Hyperspecis in the Autonomous Vehicles Industry

Hyperspec

hyperspec

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References Acknowledgments This work is financially supported by the National Key Research and Development Program of China (2017YFA0303 704), the National Natural Science Foundation of China (12274233, 62273001), the Major Scientific Research Project of Anhui Province (KJ2021ZD0005), the Compiled Scientific Research Plan Project of Anhui Province (2022AH040020), the Outstanding Research and Innovation Team Project of Anhui Province (2022AH010005), the University Collaborative Innovation Project of Anhui Province (GXXT-2021-091). References [1] Pareek NK, Patidar V, Sud KK. Image encryption using chaotic logistic map. Image Vision Comput 2006; 24:926-934. [2] Fang P, Liu H, Wu C, Liu M. A survey of image encryption algorithms based on chaotic systesm. Visual Comput 2022; 2022: 1-29. 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A fast image encryption scheme with a novel pixel swapping-based confusion approach. Nonlinear Dynam 2014; 77:1191-1207. [10] Wong K, Kwok B, Yuen C. An efficient diffusion approach for chaosbased image encryption. Chaos Soliton Fract 2009; 41:2652-2663. [11] Matthews R. On the derivation of a “chaotic” encryption algorithm. Cryptologia 1989; 13:29-42. [12] Massoudi A, Lefebvre F, De Vleeschouwer C, Macq B, Quisquater JJ. Overview on selective encryption of image and video: challenges and perspectives. Eurasip J Inf Secur 2008; 2008:179290. [13] Liu F, Koenig H. A survey of video encryption algorithms. Comput Secur 2010; 29: 3-15. [14] Chiaraluce F, Ciccarelli L, Gambi E, Pierleoni P, Reginelli M. A new chaotic algorithm for video encryption. IEEE T Consum Electr 2002; 48:838-844. [15] Lian S, Sun J, Wang J, Wang Z. A chaotic stream cipher and the usage in video protection. Chaos Soliton Fract 2007; 34:851-859. [16] Yang S, Sun S. A video encryption method based on chaotic maps in DCT domain. Prog Nat Sci 2008; 18:1299-1304. [17] Valli D, Ganesan K. Chaos based video encryption using maps and Ikeda time delay system. Eur Phys J Plus 2017; 132:1-18. [18] Kumar RR, Ganeshkumar D, Suresh A, Manigandan K. A new one round video encryption scheme based on 1D chaotic maps. in: 2019 5th Int Conf Adv Comput Commun Syst; 2019:439-444. [19] Li x, Yu H, Zhang H, Jin X, Sun H, Liu J. Video encryption based on hyperchaotic system. Multimed Tools Appl 2020; 79:23995-24011. [20] Yasser I, Mohamed A, Samra AS, Khalifa F. A chaotic-based encryption/decryption framework for secure multimedia communications. Entropy 2020; 22:1253. [21] Hosny KM, Zaki MA, Lashin NA, Hamza HM. Fast colored video encryption using block scrambling and multi-key generation. Visual Comput 2022; 2022:1-32. [22] Dua M, Makhija D, Manasa PYL, Mishra P. 3D chaotic map-cosine transformation based approach to video encryption and decryption. Open Comput Sci 2022; 12:37-56. [23] Hamidouche W, Farajallah M, Sidaty N, Assad S, Deforges O. Real-time selective video encryption based on the chaos system in scalable HEVC extension. Signal Process: Image Commun 2017; 58:73-86. [24] Chen H, Tanougast C, liu Z, Blondel W, Hao B. Optical hyperspectral image encryption based on improved Chirikov mapping and gyrator transform. Opt Laser Eng 2018; 107:62-70. [25] Fu C, Chen J, Zou H, Meng W, Zhan Y, Yu Y. A chaos-based digital image encryption scheme with an improved diffusion strategy. Opt Express 2012; 20:2363-2378. [26] Zhong J, Jiang D, Huang Q, Cao Y. A self-updating digital chaotic stream cipher. Int J Mod Phys 2018; 29:1850074. [27] Hua Z, Zhou Y. Image encryption using 2D Logistic-adjusted-Sine map. Inform Sci 2016; 339:237-253. [28] Li c, Lin D, Feng B, Lv J, Hao F. Cryptanalysis of a chaotic image encryption algorithm based on information entropy. IEEE Access 2018; 6: 75834-75842. [29] Man Z, Li J, Di X, Sheng Y, Liu Z. Double image encryption algorithm based on neural network and chaos. Chaos Soliton Fract 2021; 152:111318. [30] Kwok HS, Tang WKS. A fast image encryption system based on chaotic maps with finite precision representation. Chaos Soliton Fract 2007; 32:1518-1529. [31] Zhang X, Zhao Z, Wang J. Chaotic image encryption based on circular substitution box and key stream buffer. Singal Process 2014; 29:902-913. [32] Ye G, Wong KW. An efficient chaotic image encryption algorithm based on a generalized Arnold map. Nonlinear Dynam 2012; 69:2079-2087. [33] Rhouma R, Meherzi S, Belghith S. OCML-based colour image encryption. Chaos Soliton Fract 2009; 40:309-318. [34] Belazi A, Khan M, El-Latif AAA, Belghith S. Efficient cryptosystem approaches: S-boxes and permutation-substitution-based encryption. Nonlinear Dynam 2018; 87:337-361. [35] Wu Y, Zhou Y, Saveriades G, Agaian S, Noonan JP, Natarajan P. Local Shannon entropy measure with statistical tests for image randomness. Inform Sci 2013; 222:323-342. [36] Artiles JAP, Chaves DPB, Pimentel C. Image encryption using block cipher and chaotic sequences. Signal Process 2019; 79:24-31. [37] Xian Y, Wang X. Fractal sorting matrix and its application on chaotic image encryption. Infrom Sci 2021; 547:1154-1169. [38] Rukhin A,et al. A statistical test suite for random and pseudorandom number generators for cryptographic applications. NIST Special Publication 800-22, Revision 1.a 2010. [39] Wang X, Teng L, Qin X. A novel colour image encryption algorithm based on chaos. Signal Process 2012; 92:1101-1108. [40] Alvarez G, Li S. Some basic cryptographic requirements for chaos-based cryptosystems. Int J Bifurcat Chaos 2006; 16:2129-2151. [41] Khan M, Massod F. A novel chaotic image encryption technique based on multiple discrete dynamical maps. Multimed Tools Appl 2019; 78:26203- 26222. [42] Luo Y, Yu J, Lai W, Liu L. A novel chaotic image encryption algorithm based on improved baker map and logistic map. Multimed Tools Appl 2019; 78: 22023-22043. [43] Mansouri A, Wang X. A novel one-dimensional sine powered chaotic map and its application in a new image encryption scheme. Inform Sci 2020; 520:46-62. [44] Talhaoui MZ, Wang X. A new fractional one dimensional chaotic map and its application in high-speed image encryption. Infrom Sci 2021; 550:13- 26. [45] Chen H, Bai E, Jiang X, Wu Y. A Fast Image Encryption Algorithm Based on Improved 6-D Hyper-Chaotic System. IEEE Access 2022; 10:116031- 116044. [46] Azzeh J, Zahran B, Alqadi Z. Salt and pepper noise: Effects and removal. JOIV: Int J Inform Visual 2018; 2:252-256. [47] Gan Z, Chai X, Han D, Chen Y. A chaotic image encryption algorithm based on 3-D bit-plane permutation. Neural Comput Appl 2019; 31:7111- 7130.

Acknowledgments and References 

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I want to direct your attention to a subject of great importance, from my point of view, but often ignored: the recycling of photovoltaic panels. Have you ever reflected on the fate of solar panels at the end of their life span? The subject is not often addressed, but it deserves to be explored in depth. Therefore, I invite you to find out what the challenges of recycling photovoltaic panels are and what solutions have been discovered so far. The Current Panorama of Photovoltaic Panels Information shows us that in 2023, the photovoltaic systems market is in full expansion and innovation. Among the most recent developments are advanced photovoltaic solutions, which include high-performance materials, thermo-photovoltaic technologies, and sustainable variants. These trends are supported by decreasing costs and local production. In the USA, for example, the solar industry added 6.1 gigawatts of capacity in the first quarter of 2023, registering an increase of 47% compared to the previous year. ( ) Globally, the market was valued at 157.75 billion dollars in 2022, with a forecast of annual growth of 7.8% until 2030. ( ) source source This seems to be a positive aspect, however, we must consider a major consequence, namely the ecological impact and recycling difficulties of photovoltaic panels. Due to the high costs of recycling and limited infrastructure, you can clearly understand that many panels end up in landfills, representing a major ecological problem. However, besides protecting the environment, reusing components from used solar panels can reduce the need for raw materials, while also providing employment opportunities. Consider that in 2022, the global installed solar capacity was 268 gigawatts, an increase from 183 gigawatts in 2021, with an estimate of 315 gigawatts in 2023. ( ) What does this indicate? Of course, a future huge quantity of used photovoltaic panels. In the United Kingdom, it is estimated that solar panel waste will reach 1 million tonnes by 2050, and in Australia, they represent the fastest-growing stream of electronic waste, with over 100,000 tonnes of waste by 2035. ( ) And, as I mentioned above, the costs of recycling are often higher than those of disposal, requiring financial incentives and an adequate regulatory framework. However, Europe holds a leading role, having regulations that impose the collection and recycling of photovoltaic panels. source source Challenges and Solutions in the Recycling of Photovoltaic Panels You can easily see that the lack of an efficient system for photovoltaic panels has a major impact on the environment. Even though these panels generate clean energy, the manufacturing process and their waste at the end of the life cycle include toxic materials, which can affect the environment. Okay, then what's to be done? The most feasible and effective solutions must be found. Recycling is essential to prevent the environmental problems associated with the disposal of these panels. recycling A concrete example of recycling photovoltaic panels, or rather reconditioning, that I can offer you, is the process applied to silicon-based panels. This includes disassembling the panels into components, melting broken wafers, manufacturing new silicon cells, and final assembly, resulting in an 85% recycling rate. However, the high cost of this recycling process makes the option of landfill disposal more attractive to many decision-makers. Another process is the physical recycling process, the mechanical and most used one. In the first stage, all the materials contained in a panel are separated. These components are then ground, tested to determine the amount of toxins, and then reused. A panel can consist of various materials including silicon, glass, aluminum, copper, and silver. As for chemical recycling, which represents one of the newest solutions discovered, this is usually done after thermal treatment. It includes separating the materials of the panel through chemical processes, but this process also involves the release of dangerous gases, which represents a major issue in the recycling of photovoltaic panels. A positive thing is the possibility of reusing these substances several times in these recycling processes. To give you examples, there are two main technologies for recycling silicon-based photovoltaic panels: delamination and material separation. These technologies include dissolution in thinner, dissolution in nitric acid, thermal treatment, and ultrasonic irradiation, each with its specific advantages and disadvantages. For thin-film panels, recycling technologies include delamination, material separation, and material purification, with processes such as hydrometallurgy and pyrometallurgy, each also having its own advantages and disadvantages. ( ) source The integration of (AI) in recycling systems, including in the recycling of photovoltaic panels, represents a promising and innovative direction in waste management. If you wonder how exactly, here's the answer. A relevant example is the development, in the USA, of an intelligent waste management system, which uses smart sensors, visual cameras, and hyperspectral cameras in combination with an automatic waste sorting machine. These technologies allow capturing images of objects as they move on a conveyor belt, and sensors help monitor and control the waste management process. artificial intelligence Moreover, this technology uses machine learning models to improve the recognition and classification of non-recyclable waste. The collected information and images are uploaded to a cloud database to train and test these models, which can analyze data to identify patterns, make decisions, and continuously improve. These models will analyze the images and descriptions of waste, as well as information about the physical, chemical, and biological properties of these, to determine contaminants, energy density, and organic content. In the future, researchers plan to assess the technical feasibility and ecological performance of their system on a pilot scale. They also intend to develop a web platform that will allow them to share data sets and other information with interested parties. ( ) source Opportunities and Perspectives in the Recycling of Photovoltaic Panels Considering the complexity and costs of recycling processes, it is essential to develop more efficient and sustainable methods. Do you agree? This could include financial incentives and an adequate legislative framework, as well as research into discovering new innovative technologies in the waste recycling sector. However, this segment represents a very good business opportunity. You should know that the global market for recycling photovoltaic panels presents enormous potential, estimated to grow from 0.36 billion dollars in 2023 to 1.72 billion dollars by 2028. ( ) This opens the way for new industries focused on recycling used photovoltaic panels, and this growth is supported by numerous companies worldwide (United States, Australia, Germany, United Kingdom, Switzerland, China, Canada, Spain, Hong Kong, India, Italy, Japan, Poland, Singapore, Slovakia, South Africa, Israel, Ireland, France, and Brazil), which deal with the recycling of photovoltaic panels. source Also, various governments around the world provide funding and support for the recycling of photovoltaic panels. I'll give you a few significant examples: United States: The U.S. Department of Energy, through the Office of Solar Energy Technologies (SETO), announced the funding opportunity "Materials, Operation, and Recycling of Photovoltaics (MORE PV)" for fiscal year 2023. This will provide up to 20 million dollars over three years for research and development projects. These projects aim to create innovative and practical approaches to increase the reuse and recycling of solar technologies, thus consolidating the circular economy for in the United States. ( ) photovoltaic systems source European Union: Through EIT RawMaterials, the European Union funds a project under the supervision of Veolia Germany, with a total of 4.8 million euros. This project aims to develop an efficient and unique technology for recycling photovoltaic modules that have reached the end of their useful life. ( ) source Japan: PV CYCLE aisbl and the Akita Prefectural Resource Technology Development Organization (Akita PRTDO) announced the creation of PV CYCLE Japan for the collective management of decommissioned photovoltaic panels. The initial activity of PV CYCLE JAPAN was to serve as a point of contact for a feasibility study on the collection of decommissioned photovoltaic panels for the Ministry of the Environment of Japan, the main goal being to promote the reuse and recycling of decommissioned photovoltaic panels. ( ) source China: The Chinese government, through the National Development and Reform Commission, has announced a plan to establish a recycling system for decommissioned photovoltaic panels. By 2025, China aims to build a mechanism for disposing of decommissioned equipment from photovoltaic power plants. Also, by 2030, the Chinese government intends to mature the complete recycling system for photovoltaic power plants, while also supporting third-party recycling companies to carry out recycling activities for decommissioned photovoltaic equipment. ( ) source These initiatives reflect a significant global commitment to promoting the recycling of photovoltaic panels and to supporting the development of a circular economy in the solar energy field. I conclude that recycling photovoltaic panels is not just an ecological necessity, but also an extraordinary business opportunity. With emerging technologies and an expanding market, this field offers fertile ground for innovation and sustainable development. We face challenges, but recycling photovoltaic panels can become a path to a greener and more prosperous future. How do you see this subject?

Recycling Photovoltaic Panels: Problem or Solution?

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Lately, there has been a lot of talk about how Central and Eastern European countries are attracting the attention of investors. According to , CEE is one of the fastest-growing regions for VC funding in Europe, growing 7.6x since 2017. Dealroom And despite the from US-based investors for European in 2023, particularly those emerging from ecosystems in Central and Eastern Europe (CEE), which only make up venture capital investment, there are still initiatives aimed at securing investments for innovative startups in the region. decrease in funding startups 3.6% of the EU’s total is one of those, an event that is playing a vital role in helping the startup ecosystems of Central and Eastern Europe to flourish. This meeting point of reference for CEE entrepreneurship is serving as a platform where innovation converges with business opportunities, capital, and knowledge. Podim All roads go east The event brings together renowned international investors, established corporations, startups, and scaleups from the Alps-Adriatic and Western Balkans regions to connect and engage in efficient networking and deal-making. Recently the Podim Pitching Competition, Podim’s startup competition, announced the ten semifinalists for this year’s event. These startups come from a wide range of industries, covering everything from empowering kids and adults with hands-on experiences to creating mind-winning ads and simplifying the path to psychotherapy through video calls. STEM The ten semifinalists are CircuitMess (Croatia), Midnightdeal (Austria), Behavio and Hedepy (Czech), Radical Storage and Sensoworks (Italy), Qubinets (Croatia), NUTEK AT GmbH (Austria), Remea | EV Charging Platform (Slovenia), and eevie from (Austria). These are working on a diverse range of projects, including developing a no-code big data infrastructure platform, hyperspectral medical imaging technology, an EV charging platform, and solutions to accelerate climate action. startups Big day coming The semifinals will take place during the Podim Investors Meetup, which will be held on Monday, 15 May 2023, from 17:00 to 19:00 (local time) at the Maribox conference center in Maribor, Slovenia. The event is being held in cooperation with AWS, Credo Ventures, and South Central Ventures. During the Investors Meetup, investors, speakers, and key partners will come together to discuss the most interesting startups and entrepreneurs in the region. “At Podim, we believe that innovation is the key to unlocking the potential of the CEE region’s startup and tech ecosystem. We are proud to provide a platform that enables startups, investors, and business executives to connect, learn, and do deals efficiently. Whether you’re looking to pitch your startup, find your next business partner, or simply experience the excitement of the latest trends in technology, Podim is the place to be.”, says Urban Lapajne, Program Manager at Podim. According to their organizers, the Podim Pitching Competition provides a great opportunity for startups to showcase their ideas and receive feedback from investors and industry experts. The competition has a proven track record of helping startups grow and succeed. Past winners of the competition include companies such as Bellabeat, Celtra, and CargoX, all of which have gone on to achieve significant success in their respective industries. In addition to the pitching competition, the Podim Investors Meetup will feature a range of talks and panels on topics such as entrepreneurship, innovation, and investment. The event is a great opportunity for entrepreneurs to learn from experienced industry leaders and to network with potential investors and partners such as IDEO, ENEL, Techstars, Miro, Adidas, UiPath, Google, Infobip, and MIT Media Lab. The event will also feature 70 speakers across 14 program blocks, with highlights including discussions on defining realistic product strategy, workplace culture, and the chatbot revolution for AI startups. In addition, attendees can network with over 200 startups from the CEE and Balkan Region in the Podim Deal Room. This event promises to offer attendees the latest insights, best practices, and valuable networking opportunities. This article was originally published on . 150sec

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The skincare technology business describes itself as "the most cutting-edge skincare system in the world." A team of scientists and skincare specialists launched the company with the goal of delivering genuinely customized skin care right to your doorstep using a combination of cutting-edge technology and AI. And it actually works in a fairly cool way. In this Slogging thread, our community discussed the possibilities of AI determining your best skincare routine. This Slogging thread by Valentine Enedah, Manas Goel and Mónica Freitas occurred in slogging's official #technology channel, and has been edited for readability. Revea Valentine Enedah Oct 22, 2022, 10:54 PM Revea uses hyperspectral imaging technology (HSI) to look deep into your skin. https://mashable.com/review/revea-ai-skincare First, Revea thoroughly analyzed your skin using hyperspectral imaging technology (HSI). The company then studies your skin to "map" the unique biology of your skin and create a treatment plan that is specifically designed for you. Cool, huh? That is true, after all. Instead of relying on assumptions or oversimplified skin types like dry, normal, oily, or combination, Revea uses AI to connect the dots between your skin's data and the ideal skincare routine for you. As a result, you get a truly personalized skincare recommendation. Even if they were to build more facilities, the technology employed at San Francisco lab is pricey and not available to everyone in the world. In order to analyze your skin and receive tailored recommendations without ever leaving your home, the company decided to create a cutting-edge mobile app that enables you to scan your skin with your smartphone. The app uses artificial intelligence to link the dots between the camera on your phone and the hyperspectral imaging data. Valentine Enedah Oct 22, 2022, 10:56 PM How Revea predicts the best skincare routine? Revea's Valentine Enedah Oct 22, 2022, 11:07 PM This is so cool! ☺ What do y'all think? I don't know about you but with this, It's pretty boy season for me! Manas Goel Oct 25, 2022, 10:29 AM The AI-Driven skincare routine is a revolutionary technology indeed! Valentine Enedah. I heard about "Revea" for the first time and found it quite similar to CureSkin, an Indian startup that recently scored 5M$+ in Series A funding! I believe these technologies will attract the entertainment and the movie industry first as their use case perfectly fits the app! Also, the movie and the entertainment industry have quite a provoking influence on the youth, which again would provide a boon for such an app! However, the only fallout I believe is present here is that as this technology grows, acceptance of people to their natural aging might become a problem! , which might also bridge a gap between the rich and the poor as the rich would always look better! 💚 1 Valentine Enedah Oct 26, 2022, 7:05 AM Manas Goel Actually, we might get to that point soon that no one will want to age. But I definitely think you can't stop it. I mean your skin might look so nice but you can't stop your internal organs from aging. I hope we don't actually get to the point that we start manipulating natural processes. Mónica Freitas Oct 26, 2022, 11:46 AM Valentine Enedah once that becomes affordable, I'm there :man-running: remove my spots AI 💚 2 :rolling_on_the_floor_laughing: 2 Manas Goel Oct 26, 2022, 11:49 AM Valentine Enedah Technologies like DNA modifications have been introduced and are growing at a fast pace too! Surely with this, there'll be a point when people will stop aging! 💚 1 Valentine Enedah Oct 26, 2022, 1:51 PM Mónica Freitas 😂 Big brands like Fenty might love to collaborate with them. Valentine Enedah Oct 26, 2022, 1:56 PM Manas Goel I think there are still restrictions on DNA Modifications. It should be illegal. I actually read about a rumour that China might be using this approach to build super soldiers(hitmen). 💚 1 Manas Goel Oct 26, 2022, 1:59 PM Valentine Enedah Yes I read about the restrictions too! I'm sure it's true! China really goes out of the box, like the artificial sun!. All these inventions are really cool but scare me out so much at the same time Valentine Enedah Oct 26, 2022, 2:04 PM Manas Goel It's just mind-blowing or rather disturbing. It has good use cases but I feel the bad use cases outmatch the good ones. Being able to change the way a child would look is something. It defies all odds of nature. Feels like a simulation game. 💚 1 Mónica Freitas Oct 27, 2022, 10:25 AM Now that Rihanna is picking up her singing career again, not sure how Fenty will develop 😂 But if they can get this tech across the world to a well-known brand for a good price, that could be the way to go 💚 1 Valentine Enedah Oct 27, 2022, 12:36 PM Mónica Freitas Great point! To contribute, I think she can use her music to market Fenty products. By the way, have you seen Elon's new fragrance " Burnt Hair"? Currently sold at $100 for a piece. Mónica Freitas Oct 31, 2022, 3:44 PM Valentine Enedah she probably will in the Superbowl halftime show 😂 Is Musk hinting he's going bald? That name is suspicious hahaha Also, Musk could sell a whole world of products but perfumes won't be it Valentine Enedah Oct 31, 2022, 5:43 PM Manas Goel Actually, Elon has sold a million dollars plus worth of this perfume already. But the name though, 'burnt hair'😂 In the long run, Customers would be able to engage with and trust the metrics-based analysis of skin provided by AI face mapping technology. With the use of this skin care technology, businesses may match client needs with suggested items while letting consumers test the products' efficacy for themselves.

Can AI Determine Your Best Skincare Routine?

As nearly a thousand Earth observation satellites currently orbit the planet, terabytes of remote sensing data and satellite imagery of land, vegetation, water bodies, glaciers, urban landscapes, and other geographic features become available for end users across multiple industries. Modern GIS systems allow the collection of all such geospatial data in one place for a comprehensive analysis of the area under study. The arrival of Big Data set the stage for more advanced processing of EO datasets and garner additional insights through machine learning, predictive modeling, and other cutting-edge applications. What Is Behind the Booming GIS and Big Data Applications? Big Data technology enables users to manage and process vast amounts of versatile data (for example, satellite pictures of Earth), which is getting bigger by the day. The convergence of GIS and Big Data was a matter of time and tech progress, as their union opens up immense opportunities for businesses and individuals alike. Many organizations are gaining value with geospatial big data analytics to tackle existing issues and improve decision-making and future planning. Ten years ago, the high price of hardware computing resources was the main barrier that kept many from using Big Data. Today we see more affordable hardware costs and have access to scalable cloud products, which altogether makes this technology available to anyone, from large governmental institutions to tiny private businesses. The present challenge is about talents; not everyone has the expertise required to leverage big chunks of data to the benefit of their companies. The Many Applications of Earth Observation Imagery Satellite images of Earth have proved their unrivaled value in multiple domains, including agriculture, forestry, environment, disaster relief, intelligence, defense, and urban planning among dozens of others. Here’s looking at some less-known industries that are leveraging the ability of remote sensing to reveal what the human eye can’t see. Investigative Journalism Over the past years, satellite images of Earth have become frequent in the news media providing a deeper context for the tragedies occurring on the ground. With the help of remote sensing satellite data, not only can we see the consequences of destructive natural or manmade disasters and pinpoint where illegal forest clearing or fishery is made, but also get clues about what or who is responsible for the damage done in war conflicts, and even find better solutions for mitigating the impacts. Bellingcat is one good example of how a group of journalists can make some eye-opening discoveries about international conflicts based on freely available geospatial data. Through the mediation of Earth observation specialists, journalists can access one more source of relevant and up-to-date information for their stories, which is satellite imagery. Air Pollution Geospatial data has been widely used to monitor various environmental issues, such as deforestation, melting glaciers, water bodies polluted by oil spills, and so on. No wonder there are known applications in air pollution studies as well. As we know, agriculture accounts for the largest portion of harmful NH3 (ammonia) emissions, which are only expected to rise with more ammonia plants set for opening across Asian and Middle East countries by 2030. The slurry that is stored in tanks until it’s ready for application as fertilizer is the main source of ammonia. One of the recent use cases is the collaboration of the Danish government and a satellite data provider to estimate the country’s total NH3 emissions. The combination of machine learning and the most up-to-date satellite images of farms helped to detect 26,000 slurry tanks in Denmark within hours. With internal data on each farm and its production type at hand, they were able to produce a countrywide estimate of ammonia emissions coming from slurry tanks. Mining Satellite pictures of Earth captured by multispectral and hyperspectral sensors can benefit exploration geologists and scientists too. At the very least, geologists can gather reflection data and absorption properties of various soil types, rocks, and vegetation cover to differentiate between the Earth’s surface features. On a more advanced level, certain spectral bands can be used at several stages of . Mining companies that rely on spectral analysis of satellite data save time and costs as it helps narrow down the search and map the potential areas with mineral deposits. mineral mapping and exploration The current amount of GIS data in our hands is overwhelming. It takes the form of remote sensing imagery, real-time satellite view feeds, topographic maps, LiDAR and inSAR data, and others, providing a myriad of opportunities for use. Knowing one’s way around huge datasets and being able to extract value for each particular industry with existing solutions presents one of the main challenges for modern GIS specialists.

Big ‘Earth Observation’ Data: Challenges and Applications

Earlier this month, the European Union Parliament aimed at limiting how companies and websites can track people online to target them with advertisements. Targeted advertising based on people’s online behavior has long been the business model that underwrites the internet. passed sweeping new rules It allows advertisers to use the mass of personal data collected by Meta, Google, and other tech companies as people browse the web to serve ads to users by sorting them into tens of thousands of hyperspecific categories. But behavioral advertising is also controversial. Critics argue that the practice enables discrimination, potentially only . They also say serving people ads based on what big tech companies assume they’re interested in potentially leaves people vulnerable to , , and . offering certain groups of people economic opportunities scams fraud disinformation Notoriously, the consulting firm Cambridge Analytica to target certain Americans with pro-Trump messages and certain Britons with pro-Brexit ads. used personal data gleaned from Facebook profiles The 2016 U.S. presidential election and the Brexit vote, according to Jan Penfrat, a senior policy adviser at European digital rights group EDRi, were “wake-up calls” to the Europe Union to crack down. Lawmakers in the U.S. are also looking into ways to regulate behavioral advertising. ↩︎ link What Will the European Parliament’s New Regulations Do? There’s been a long back and forth about how much to crack down on targeted advertising in the Digital Services Act (DSA), the EU’s big legislative package aimed at regulating Big Tech. Everything from a total ban on behavioral advertising to more modest changes around ad transparency has at some point been on the table. On Jan. 19, the Parliament . Included is a ban on targeted advertising to minors, a ban on tracking sensitive categories like religion, political affiliation, or sexual orientation, and ” for access if users opt-out of their data being tracked for targeted advertising. approved its final position on the bill a requirement for websites to provide “other fair and reasonable options The bill also includes a ban on so-called —“design choices that steer people into decisions they may not have made under normal conditions—such as the endless clicks it takes to opt out of being tracked by cookies on many websites.” dark patterns That measure is critical, according to Alexandre de Streel, the academic director of the think tank Centre on Regulation in Europe, because of how tech companies responded to the General Data Protection Regulation (GDPR), the EU’s 2016 tech regulation. In a study on online advertising for the Parliament’s crucial Committee on the Internal Market and Consumer Protection, de Streel and nearly a dozen other experts ” had become a major tool used by websites and platforms to persuade users to provide consent for sharing their data. documented how “dark patterns Their recommendations for the DSA—which included more robust enforcement of the GDPR, stricter rules about obtaining consent, and the dark patterns ban—were included in the final bill. “We are going in the right direction if we better enforce the GDPR and add these amendments on ‘dark patterns,’ ” De Streel told The Markup. German member of European Parliament Patrick Breyer joined with more than 20 other MEPs and more than 50 public and private organizations last year to form the . Though its push for a total ban on targeted advertising failed, the coalition was behind many of the more stringent restrictions. Breyer told The Markup the new rules were “a major achievement.” Tracking Free Ads Coalition “The Parliament stopped short of prohibiting surveillance advertising, but giving people a true choice [of whether to be targeted] is a major step forward, and I think the vast majority of people will use this option,” he said. The EU that could potentially be more stringent around targeting and using personal data. will address digital political advertising in a separate bill Despite passing the European Parliament, the DSA is far from settled. Due to the EU’s unique law-making process, the legislation must now be negotiated with the European Commission and the bloc’s 27 countries. The member states, as represented by the European Council, have adopted an official position considerably less aggressive— —and, according to Breyer, are “traditionally very open to [industry] lobbying.” opting for only improved transparency on targeted advertising Whether the DSA’s wins against targeted advertising survive this process “will depend to a large degree on public pressure,” said Breyer. How Has Big Tech Responded? So far, Big Tech companies have publicly tread lightly in response to the European push to limit targeted advertising. In response to The Markup’s request for comment, Google spokesperson Karl Ryan said that Google supports the DSA and that it shares “the goal of MEPs to continue to make the internet safer for everyone….” “We will now take some time to analyze the final Parliament text to understand how it could impact us and our different users,” he said. Meta did not respond to a request for comment. But privately, over the last two years, Google, Facebook, Amazon, Apple, and Microsoft in Brussels, spending more than $20 million in 2020. have ramped up lobbying efforts The advertising industry, meanwhile, has been public in its opposition. In , Interactive Advertising Bureau Europe director of public policy Greg Mroczkowski urged policymakers to reconsider. a statement on the recent vote “The use of personal data in advertising is already tightly regulated by existing legislation,” Mroczkowski said, apparently referencing the GDPR, which regulates data privacy in the EU generally. He further noted that the new rules “risk undermining” existing law and “the entire ad-supported digital economy.” On Wednesday, the Belgian Data Protection Authority found IAB Europe–which developed and administered the system for companies to obtain consent for behavioral advertising while complying with GDPR—in violation of that law. In particular, the authority found that the pop-ups that ask for people’s consent to process their data as they visit websites failed to meet . GDPR’s standards for transparency and consent The pop-up posed “ ” of Europeans, the ruling said. The authority ordered IAB to delete data collected under its Transparency and Consent Framework and has six months to comply. great risks to the fundamental rights “This decision is momentous,” Johnny Ryan, a senior fellow at the Irish Council for Civil Liberties, told The Markup. “It means that digital rights are real. And there is a significance for the United States, too, because the IAB has introduced the same consent spam for the CCPA and CPRA [California Consumer Privacy Act and California Privacy Rights Act].” , IAB Europe said it “reject[s] the finding that we are a data controller” in the context of its consent framework and is “considering all options with respect to a legal challenge.” Further, it said it is working on an “action plan to be executed within the prescribed six months” to bring it within GDPR compliance. In a statement to Tech Crunch Google and Meta may be preparing for whichever way the wind is blowing. Google is , which stores general topics of interest in a user’s browser while excluding sensitive categories like race. Meta a protocol to target users without using tracking cookies. developing a supposedly less-invasive targeted advertising system is testing A handful of European companies like internet security company Avast, search engine DuckDuckGo (which is a contributor to The Markup), and publisher Axel Springer see tighter rules around data privacy or tech that matches ads based on a website’s content, and to therefore break the Google-Meta duopoly over online advertising. as a means to push the industry toward contextual ads What’s Happening in the U.S.? On Jan. 18, Reps. Anna Eshoo (D-CA) and Jan Schakowsky (D-IL) and Sen. Cory Booker (D-NJ) to prohibit advertisers from using personal data to target advertisements—particularly using data about a person’s race, gender, and religion. Exceptions would be made for “broad” location information and contextual advertising. introduced legislation to Congress “The hoarding of people’s personal data not only abuses privacy, but also drives the spread of misinformation, domestic extremism, racial division, and violence,” Booker in January. said in a statement announcing the bill While there is a bipartisan desire to rein in Big Tech, there is no consensus on how to do it. The bill is designed to stop Amazon, Apple, Google, and other tech giants from . Congressional action on targeted advertising does not appear likely. most likely to pass the divided Congress privileging their own products Still, it is possible the Federal Trade Commission will take action. Last summer, President Biden issued an directing the FTC to use its rulemaking authority to curtail “unfair data collection and surveillance practices.” In December, the FTC for a petition by nonprofit Accountable Tech to develop new data privacy rules. executive order sought public comment Meanwhile, many U.S. digital rights activists, , are hopeful that new rules in Europe , as occurred after the GDPR. such as the nonprofit Electronic Frontier Foundation will force changes globally “The EU Parliament’s position, if it becomes law, could change the rules of the game for all platforms,” wrote EFF’s international policy director Christopher Schmon. It’s still early days, but many see the tide turning against targeted advertising. These types of conversations, according to Penfrat at EDRi, were unthinkable a few years ago. “The fact that a ban on surveillance-based advertising has been brought into the mainstream is a huge success,” he said. Written by: Harrison Jacobs Photo by on Tânia Mousinho Unsplash Also published here

Could There Eventually Be a Ban on Behavioral Advertising?

[Pic] The classic legend of dual-use nature exploiting institutional ambiguities, sitting in the ruins of a medieval empire. A couple of years ago, the US put a worldwide export control on convolutional neural network based geospatial imagery software, the reason being its potential use by foreign militaries. It is worth noting that these are commercial software products which if open-sourced, their hardware dependencies aside, would not be treated under international jurisprudence as products but instead as free-speech. Which brings us to the subject of export controls, dual-use emerging technologies, and legacy international institutions. quietly Technology Export & Information Export-control in itself is an old and important tool of statecraft, serving economic as well as military functions. However the present dichotomous classification of technologies based on military and non-military usage is severely outdated and in fact only holds-up when dealing with conventional weapons. AI in itself isn't a weapon but an enabler and having AI-superiority proves hugely advantageous when extending general capabilities across all kinds of defense systems and platforms, giving the machine learning software-stack and hardware accelerators a strong military utility. To deal with the problematic usage of such dual-use technologies, the most prominent international regime is the . The arrangement, with respect to its fundamental role of helping to prevent the malicious use of technology, is pretty ineffectual when it comes to Artificial Intelligence and its ICT based applications. The de-territorializing effects of cyberspace present a clear institutional, regulatory, and compliance gap, where arrangements like Wassenaar only end up imposing yesterday’s standards over tomorrow’s technology. For example the first time when Wassenaar was invoked, it targeted software during the 90s to stop international adoption of cryptographic techniques over things like e-mail communications. That turned out to be a lot more than just diplomatic failure. Wassenaar Arrangement And Wassenaar isn't the only international regime facing difficulty with technological changes. The MTCR (Missile Technology Control Regime) for example has been updated to include long range UAVs and future changes sooner than later. It must be made clear that these controls do not work as intended. There is always great difficulty in enforcing contracts in emerging markets, there is an ever-present tradeoff between transparency and secrecy, and moreover in an environment of deception the compliance can not be truly verified even if states bring (they do) their own technical means of verification. This is a grand version of what game theorists call a POSG (Partial Observation Stochastic Game), really fascinating and quite intractable stuff. will need Scholars have duly noted the inherent in Wassenaar Arrangement, especially when dealing with intangible dual-use technologies. There is no consensus on whether the arrangement could adapt to technologies which are both socioeconomically foundational and militarily significant, without ironically turning itself into a dual-use multilateral instrument of coercive and economic statecraft. ambiguity Such concerns are not unfounded in international politics, take for example when in 1993 the Americans got the Russians to cancel the transfer of cryogenic technologies to India in for some US-Russia space cooperation. Software being fundamentally information, presents more compounded challenges for export controls given the largely unregulated flow of information across borders. Basically the trouble being that if you put sanctions over the export of fishes to someone, failing to prevent him from learning to fish is a foreign policy failure. exchange Not surprisingly therefore, a recent US AI-policy which declared advertising-technologies as "NatSecTech", also contained that "Export controls should be utilized... to slow competitors’ efforts to develop indigenous industries in sensitive technologies with defense applications... (by) targeting discrete choke-points." report Proliferation & The Undefined The Mahabharat is absolutely filled with instances of specialized and more devastating tools being limited-by-distribution to only select few, though those familiar with the text would concur that this non-proliferation regime did little to control privileged actor behavior and eventually an utterly morbid devastation followed up. Multilateral export control regimes today pursue a deterrence by denial framework towards global security. However, in case of ICT based goods when export controls suppress economic interests, proliferation shifts to a black market, even between member states, on shady darknet sites. It takes no genius to see that legally binding restrictions on AI capabilities will be economically debilitating, so it is going to be really hard to enforce sovereignty over technology or even know which exact technologies to control. Let us consider a hypothetical scenario: Most of the (>90%) in AI operation happens due to what can be described as "data movement operations" — adjusting features, weights, biases, transferring intermediate results etc — so it is understandable that a  better power management technique/toolkit could make the systems significantly more energy efficient. power consumption Now consider that in a not-too-distant future these computations are happening in autonomous edge devices fielded on both sides amid a lengthy military standoff in a remote inhospitable region such as the deserted upper reaches of the Himalayas. Would an innovative intangible power model here be treated the same way an advanced battery technology is treated? What if someone strategically open-sources it? Given that even technologies used today in public transportation, agriculture and pollution monitoring, such as LIDAR and hyperspectral tracking, will be very easily directed to military usage; several researchers have to use the phrase "omni-use" to describe AI and other related emerging ecosystem. It should be clear to whomsoever-it-may-concern that they cannot control the flow of omni-use intangible items and neither can it be ascertained decidedly what or from who an omni-use technology must be kept. In an area like this, traditional controls will only bring about regulations and more of other unsavory economics. suggested shadow Way Forward, Institutional Corrigibility Most countries with strong R&D focus prefer their weapon-systems to be approached as black-boxes, not to be reversed engineered or subjected to exhaustive component analysis. On another side, in future insurgencies and urban conflicts, we could be seeing a lot of improvised weapon systems which utilize open-source and low cost OTS components, those which would just not be regulated with current approaches. What technologies are available to militaries greatly guides how societies evolve and technologies also have a tendency to become more efficient relatively quickly because of their near-constant evolutionary cycle of adaptation and reinvention. It is therefore fitting and important to have a better and continuous coupling with all stakeholders, and not get carried away by media headlines, trends and lobbying. So building Institutional in our context can be thought of as designing mechanisms to facilitate objective stakeholders (from academia and industry) bring necessary outside correction in transgovernmental networks responsible for developing and implementing technology export controls. Corrigibility The multilateral international institutions must understand and absorb the difference between essential system complexity and accidental system complexity, and work every bit to minimize and first and obliterate the second. Previously published at https://muskdeer.blogspot.com/2021/03/the-narcissism-of-technical-differences.html

On Export Controls And Dual-use Emerging Technologies

It used to be that when someone heard the term “drone” the first thing they thought of was militaries flying unmanned aerial vehicles (UAV) over hostile territory to record valuable information or potentially even deploy weapons. With the advent of recreational drones, the focus has shifted, with many associating drones with fun, outdoor activities. Now, with significant increase in the consumer and commercial drone markets, there’s an entirely new set of potential implementations for the technology and the people utilizing it. North America Consumer Drone Market By Technology, 2012–2022 (USD Million) Consumer Drone Market Analysis By Product, Grand View Research The market for consumer drones has been growing consistently over recent years, especially after the Federal Aviation Administration (FAA) in the US was brought to court in response to an original decision requiring recreational owners to register their drones. Upon review, a and stated that recreational drone users would not need to register their drones. Now, a from the Trump administration requires owners to register, yet again. However, even with the on-again, off-again relationship with the FAA, drone enthusiasts are still involved in their hobby in large numbers. In 2016 it was reported that drone sales tripled in one year alone, according to research from . Ben Arnold, executive director and industry analyst for The NPD Group said in a that the growth can be attributed to many new uses for drones. federal appeals court deemed the program unlawful recent bill The NPD Group statement along with the published research “The drone category is continuing to take shape as new products and features such as 4K cameras, Bluetooth and built-in GPS, reveal an expanding range of use cases. The market is maturing in that respect.” With the growing market size and increased amount of uses across the board, drones aren’t just for fun anymore. Though they’re still great for capturing that perfect shot of the family campsite, here are 5 industries that drones are transforming. Cinematography (by on ) William Stitt Stocksnap The film industry is one area that likely isn’t going to come as a surprise to most. Out of all the possible uses of drones, filming with the small unmanned aircraft is one of the crucial functions of such devices. As camera and recording technology continues to improve and be made smaller, lighter, and easier to attach to aerial vehicles, the benefits of using drones in the film industry grow nearly exponentially. For filmmakers, there are two distinct advantages of drones on sets: versatility and cost-efficiency. Unlike traditional filming from the sky (think ), drones can film in extraordinary spaces and capture unique shots not previously accessible. Filmmakers are able to use drones to get distinct shots in narrow spaces like alleyways and canyons and operate much closer to the ground than a traditional aerial film crew (for example: drones can record flying through windows and doors then smoothly transition to an aerial shot). Good luck trying to fit an through a dense forest or office window. camera crew in a helicopter H125 The other advantage drones bring to the film industry is cost-efficiency in a major way. Because of how much more affordable drones are (you can pick up a Phantom 4 “Ultimate Bundle” for under , whereas an H125 starts in the high six figures and low seven figures), so production crews can purchase the equipment on their own without breaking the bank. Or, if their budget is even tighter, production crews can hire licensed drone operators who specialize in filming for an even lower price to film the footage needed. While drones and recording needs, there are plenty of times during shooting where a helicopter‘s job can be done instead by a drone. Combine that with the cost savings and the barrier to entry for the aerial filming, and the market is drastically reduced, opening up opportunities for smaller production teams. $2,000 on Amazon can’t handle all conditions Alternative Data Collection In the financial space, so-called “alternative data” is growing in popularity. Alternative data refers to any kind of data investors can use that comes from a nontraditional source and provides additional insight into a prospective investment. While companies will hand over relevant information to investors, there are additional ways of gaining insight come directly from the standard financial paperwork. Drones are playing an increasingly important role in the growing sector for alternative data because of their versatility. Alternative data includes a wide array of information like parking lot traffic at any given retail location, the status of mining operations, land development, and nearly anything else investors may be interested in. It’s clear that drones can collect impressive amounts of data, though currently this drone usage is still in its infancy. With the ability for drones to offer cost-effective, highly accurate data to investors, this is one area that Quandl, one of the leading providers of alternative data in the financial sector, is . keeping an eye on for future developments Geospatial Drone footage is able to provide an incredible amount of not just data, but also detailed information about geographical locations as well. Unlike satellites, which are expensive and greatly affected by weather conditions like rain, clouds, and darkness, drones are versatile, more cost-effective, and can collect geographical data in less than ideal conditions. Because of the benefits of operating drones, it’s now much more practical to collect real-time, accurate information. Drones are already in use offering detailed images and information for HD mapping, a necessity for the incoming wave of autonomous vehicles that require more sophisticated maps. As Leslie Hook with the puts it, these cars “need a map, but not just any map — these cars need a three-dimensional representation of the environment around them, one that is updated continuously and is accurate down the centimeter.” Financial Times Companies like are using a combination of drones and on-board devices to create detailed maps that will be a necessity in the near future to aid self-driving vehicles, while others like are studying the use of drones to actually guide the vehicles in question. Sanborn Ford Outside of the realm of autonomous vehicles though are new ventures such as Soar, which is leveraging the usage of drones to develop the geospatial industry as well, though taking a bit of a different approach. is a blockchain-based startup looking to create the world’s first decentralized global super-map using drone content contributed by users in the network. Users on the platform can use their own drone footage and information generated to update a massively detailed global map (i.e. a “super-map). Being , all information about the timing, location, and content creator of recorded footage will be immutably written on the blockchain for future reference ensuring accountability. This decentralized, blockchain-based approach is using drones and the global community to crowdsource the creation of the most detailed super-map of the Earth. It’s quite an ambition, but drones are one of the key driving forces that can make it happen. Soar blockchain-based Currently, the closest we are to a “Super map” is Google Earth, which is great for getting a large view of the globe and some streets, but when introducing drone content to the equation, users will have a far more detailed picture of the entire globe with offerings unavailable from traditional satellites. Manufacturing Though it may not be the first thing that comes to mind when you think about drones, the new UAVs are making their way to the manufacturing process as well. Often we might think about robots taking over the production process of good (think robotic arms assembling vehicle components), but there’s room for drones along the way as well. What we’re seeing now is the introduction of drones for nearly every step of the manufacturing process including warehouse organization, inventory control, and supply chain management to aid the rest of the process. Some of the biggest examples of drones in the manufacturing process include inspecting and monitoring quality. In the warehouse, drones using a variety of methods including barcodes, QR codes, or RFID. And that’s really just the beginning of their use. With the internet of things (IoT) constantly developing and becoming more integrated, we could likely see drones running all kinds of tasks in the production process to maximize efficiency and safety for workers. Just look at where Amazon is potentially . measure inventory and keep records up-to-date headed in the near future Agriculture Last but not least is the agricultural industry. Agriculture has been one of the top industries to capitalize on the advancement of drones and the opportunities they provide. With their ability to collect alternative data, create detailed 3D maps, and perform tasks in a much more cost-effective manner, the uses for drones in agriculture are numerous. According to , of the vast number of drone possibilities in agriculture, some of the biggest benefits that stand out include soil and field analysis, planting, crop spraying, monitoring, irrigation, and health assessment. New drone-related startups have created drone-planting systems that are estimated to save producers on planting costs by up to 85% because of their efficiency. In fact, the startup which is working with the in Myanmar, is supplying drones capable of planting as many as . That’s an efficient process. MIT BioCarbon Engineering, Worldview International Foundation 100,000 trees in a single day In addition, drones are able to report real-time information about the health and development of crops as well as record information using hyperspectral, multispectral, or thermal sensors about which areas of the property are dry and need improved irrigation. This information can then be used to make proper adjustments to ensure the highest efficiency possible and reduce waste. There are vast implications for the growing tech trend outside of recreation that mean big things for the rest of the economy. From the film industry to agriculture, there are uses for drones in essentially every industry imaginable. Beyond these five fields, drones are being used by governmental organizations, building and monitoring infrastructure, transporting goods, and really any other business you can think of. Have you thought about drone implementation in industry? your

Pleasure and Business Merge, Here Are 5 Industries Drone Tech Is Transforming

There is a trend in neural networks that has existed since the beginning of the deep learning revolution which is succinctly captured in one word: scale. The natural dimensions of scaling these models have been compute and data. Compute scaling has been a massive undertaking at every level of the stack, from hardware accelerators to high-level software tools, for more than a decade. Large datasets have become a key advantage in the new digital economy, and it has been the driver behind models that can ingest and make sense of such datasets. In most cases the best models are at the cutting edge of our ability to scale on these resources. This becomes a practical issue as predictions sometimes need to be computed at high volume with low latency, but generally the models that learn the best aren't the fastest. The field of study that relates to tackling this issue is called model compression. There are many techniques, some feeling a little hacky like setting small weights to zero and inducing sparse data representations. Others seem more principled like knowledge distillation, where a trained heavy-weight model is used to "teach" a much smaller network, or another technique called conditional computation where a controller decides which parts of a network to activate for a given input sample. Model Adaptation and Decompression It's an open question as to how much compressed models lose in generalizability versus the originally trained network. If you read the papers you'll of course see that in the experiments the compressed models perform just as well or surprisingly even better than the original models on their evaluation sets. But one thing I've learned in deploying models in the real world is that it's never the end of the story. The environment can always change under you, sometimes slowly and sometimes rather quickly. The road to truly intelligent and adaptive systems might rely on what I've been inspired by the old gods of creativity and genius to call . The principle is straightforward: when you detect your model drifting in its performance, add back some capacity in the compressed model and learn on the fly. model decompression This sounds like a stupid idea from a technical standpoint because the way we deal with model drift today is much more effective. We just retrain or continually train the big network and repeat the compression process when we want to ship out a new model. Understanding why is the suboptimal thing requires a bit of imagination with respect to edge computing. that The Edge The reason model compression gets any sort of real attention is because we want to deploy these amazing technologies without being bottlenecked by networks. Network communication is typically the slowest and worst resource to be limited by, so if you need a heavy cloud server to do all of your ML and send it back to a mobile phone or remote device you're going to have a bad time with reliability and latency. Model compression enables us to ship these models and run them on-device with low latency and low power consumption. I'll walk back on calling our current methods silly a bit because when the environment changes radically you can't expect a hyperspecialized model to simply adapt itself completely. If that were true we would never need a heavyweight model to begin with. There is some recent work on using intermediate models, called "teaching assistants", to help build a hierarchy of distillation to help the student network learn better. Taking this to its logical end for solving model drift at the edge, it seems that the intermediate networks can sit on a spectrum of resource requirements between the teacher and the student. Of course for smaller drift this makes a lot more sense, and perhaps one could even get away with no new resources at all (besides compute power). It is all relative, and something that humans in the form of ML engineers shouldn't be tuning themselves when they're alerted that the models are suddenly regressing. It makes a lot more sense that we introduce new components to this system that help automate this process. There have been a lot of criticisms thrown at our distinction between a training and inference phase. The thought is that training should always be happening like in brains, not just one-and-done. This is somewhat related to the study of . continual learners Unfortunately this doesn't easily fit with the hardware story. Training is assumed to be very compute intensive, and the situation is rather hopeless without hardware acceleration. But this isn't always the reality: training is known to be compute intensive, but we may not need dozens or hundreds of passes over our training data to adapt to new situations. Perhaps it's worth revisiting the idea of training at the edge with current hardware. from scratch Next-Generation Neural Systems These are hard problems to solve today for the edge because of the hard constraints on resources. They are much less encumbering in the cloud, so it's a wonder why we don't have systems that auto-tune themselves and constantly ingest data from a variety of streams. Well, we have them, but of the organizations I know that do this the size of their ML teams is in the dozens to hundreds. One big reason is just that building scalable data processing systems is still non-trivial. But the bigger reason is that our models are still hard to train, for a variety of reasons, and it involves a lot of people trying different ideas to make gains in performance. This makes sense in the age of ML where features are generated by hand. But deep learning has changed that, or at least it promised to. And we have shown in the past decades, especially our most recent one, that this does work. But most real-world scenarios haven't had the benefit of some very bright scientists and years of research thinking about inductive biases and data preparation strategies. Scaling their efforts has resulted in things like neural architecture search, hyperparameter optimization, and transfer learning. These have also been proven to work internally at Google, so much so that it's now available as a cloud service. With newer forms of unsupervised pretraining methods in different data domains, the canonical successes of deep learning may finally be realized for many real world problems across domains and industries. These are the foundational elements of our next-generation system. Barriers As of yet these elements are not integrated into one system. There are several reasons for why we haven't gotten there which I will outline. Some of the parts seem incompatible. For instance, after finding an optimal architecture via neural architecture search, how does one then employ transfer learning from pretrained models? And is there software out there where you can store models and query them when you want to build a new one, retrieving the best one to use as a pretrained starting point? Do similar things exist for getting raw data into the optimal form for current networks to effectively learn from? Surely those algorithms exist with hyperparameter equivalents that should be tuned in conjunction with models? I expect in time we will solve some of these things, and it's something that must be driven by an industry research lab with the expertise in both systems engineering and deep learning as a science. There is also a large cost to running such a system, ignoring the necessary upfront capital to build it. But cost is less interesting if we expand our view on the time dimension. Because everyone knows that compute costs will always trend aggressively downwards, it has been true for half a century now, it continues despite the end of Moore's Law, and there is now an entire global economy pushing that advancement along. Cost is also less interesting because transfer learning promises to remove the bulk of necessary compute power. One only needs to train a good base model once and fine-tune it as many times as necessary with cost being orders of magnitude smaller. This evokes the application of another advanced technique in the area: federated learning. It is often the case that companies have proprietary data they don't want to share. And yet they may also be hesitant to exploit that data due to the severe cost limitations on apply deep learning to it. But perhaps they would be more willing if we had our next-generation adaptive deep learning system coupled with the ability to do federated learning, that is, train locally (as in, on-premises inside a company's network) and only report back gradients to the outside world. Concretely, this could enable multiple health records companies or law firms to jointly create the best model for their problems, leaving its true application downstream for fine-tuning on their specific problems where they don't have to share anything about the model (and the other parties likely don't care much for it anyway as it's of only tangential value to them). Federated learning could drive the cost of even the initial pretraining models down further. Perhaps we need not wait for better compute hardware after all.

What's Next for Adaptive Neural Systems?

Born under a bad sign — AI learning, trolling, economy & political influence — leads to unwanted developments and consequences. Shape of things to come — health privacy, insect bots & chip making — is a mixed bag of developments. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Born under a bad sign - DARPA Seeking AI That Learns All the Time — “[DARPA] is looking to change the way works…[with] …that learn continuously, adapt to new tasks, and know what to learn and when. ‘ AI Lifelong Learning Machines …. We want the rigor of automation with the flexibility of the human’ ….[ Neural networks are adaptable systems whose ability to learn comes from…[training] on a set of data….[Problem] when the AI encounters something it was never trained to recognize So] two sets of groups. One set will…develop systems that can continuously learn, adapt to new tasks and circumstances, and understand inputs according to what the system’s mission is (called ‘goal-driven perception)…. .” [Another] to identify new mechanisms of lifelong learning — from biology or a physical science — and transfer that mechanism to an algorithm that improves AI https://spectrum.ieee.org/cars-that-think/robotics/artificial-intelligence/darpa-seeking-ai-that-can-learn-all-the-time _There are ghosts in the machine._medium.com Why You Should Fear Artificial Intelligence-AI State-Sponsored Trolling — “[T]he use by states of targeted online hate and harassment campaigns to intimidate and silence individuals critical of the state…[using] surveillance and hacking…afforded by a new era of pervasive technology…persecutes perceived opponents at scale…. [ …. There’s] several commonalities…[including] death and rape threats, using bots…to amplify vitriolic attacks at scale…accusations of treason or collusion with foreign intelligence agencies, using ‘black’ public relations firms to disseminate hyper-partisan or libelous disinformation about targets, spreading doctored images and memes…using spyware and hacking to gather…intelligence against targets, and sowing acrimonious sexism ….[ Changes in law are unlikely to effectively stem the practice of state-sponsored trolling in the short term…[so] technology companies bear…[responsibility] to curb…state-sponsored harassment campaigns…[as] form of human rights abuse…with pinpoint personalization Need] the expansion of…international and US law to include the types of online harassment and hate speech deployed as part of state-sponsored trolling attacks; the reconsideration of intermediary liability…[for] platforms in facilitating trolling campaigns;… .” technology companies to detect and identify state-linked accounts, bots, and hateful content online http://www.iftf.org/fileadmin/user_upload/images/DigIntel/IFTF_State_sponsored_trolling_report.pdf These 3 advantages once ensured U.S. prosperity. They’re not coming back. — “[Prosperity] constructs a society with greater economic and social justice…[Trump’s] appeal rests heavily on our loss of confidence in this vision…. From 1950 to 1973, the economy grew at an average annual rate of 4 percent …[but] from 2008 to 2017…averaged only 1.5 percent ….[T]he postwar boom…[had] three economic advantages…that were fated to fade…. backlog of new technologies (television, jet aircraft, synthetic fibers, antibiotics, air conditioning) that boosted both consumer spending and business investment…. destruction of Europe and Japan left…few serious [competitors]…[so] trade balance was routinely in surplus; the first deficit [1971]…. …. …. progress in stabilizing the economy 2008–2009 financial crisis remind us that the problem of the business cycle hasn’t been solved …. U.S. corporations turn out to be vulnerable…abroad, and to new technologies…. The skewing of income toward those at the top compounds the effect…[and] a breeding ground for discontent ” Trump blames… immigrants and imports…[and] American officials…[so] tariff proposals seem to be causing as much or more grief among the U.S. firms they’re supposed to help…[because] there’s a big difference between economic nostalgia and economic policy. https://www.washingtonpost.com/opinions/these-3-advantages-once-ensured-us-prosperity-theyre-not-coming-back/2018/07/22/835b4102-8c49-11e8-a345-a1bf7847b375_story.html?utm_term=.75d1f0c9de66 _As a dog that regularly bites, it is fair to say we have a love-hate relationship with capitalism. This lends itself to…_medium.com Capitalism and Post-Capitalism — The Whole Truth & Nothing But As inequality grows, so does the political influence of the rich — “SQUEEZING the top 1% ought to be…[easy] for politicians seeking to please the masses…[but] more concerned with immigration and sovereignty…[is] sign of the corrupting influence of inequality…. …. 19th century governments across the West faced the threat of socialist revolution…[and] promises of greater redistribution…[needed] institutional guarantees America’s electoral college…prized by elites…because they served as a check on the egalitarian tendencies of the masses …. …. [Today] more than two-thirds of Americans and Europeans express concern about current levels of inequality…[but] democracies might have become too jammed to make progress on any issue of substance …. Last year America’s government…change to taxes…tilts the distribution of income even more in favor of the rich…[and] politicians seem less interested in grappling with the problem [ So] rising inequality…boost the power of the rich…to counter the popular will…[with] political preferences of those with $40m or more…overwhelmingly favor cutting spending on major social-safety-net programs. (The general public wants it increased.).… [In] regular personal contact with elected officials…fewer than 30,000 people account for a quarter of all national political donations from individuals and…more than 80% of the money raised by political parties…[with] means to shape public opinion: financing…think-tanks…or buying media outlets…to shape public narratives about which problems deserve attention…[so] economic justice are crowded out…. [It’s] the ‘negative agenda power’ of the rich…that reducing inequality becomes less likely even as it becomes more urgent…with a loss of democratic accountability as a nasty side-effect …. [So far] across human history, inequality inevitably rises until checked by disasters like wars or revolutions…. If political leaders tried…they might…find that redistribution is a winner at the ballot box.” https://www.economist.com/finance-and-economics/2018/07/21/as-inequality-grows-so-does-the-political-influence-of-the-rich Shape of things to come — Health Insurers Are Vacuuming Up Details About You — And It Could Raise Your Rates — “[Insurers] are tracking your race, education level, TV habits, marital status, net worth**… ….** social media, whether you’re behind on your bills, what you order online…[then] feed this information into…algorithms that spit out predictions about how much your health care could cost them …. [But] patient advocates and privacy scholars say the insurance industry’s data gathering runs counter to its…federally required, allegiance to patients’ medical privacy …. HIPAA only protects medical information Patient advocates warn that using unverified, error-prone ‘lifestyle’ data to make medical assumptions could lead insurers to improperly price plans — for instance, raising rates based on false information — or discriminate against anyone tagged as high cost …. . . [This] is important because patients — through taxes, cash payments and insurance premiums…[fund] entire health care system Yet the industry’s…strategies and inside deals often has little to do with patients’ needs… [ …. T]he big guns in health data…[are] Optum, IBM Watson Health and LexisNexis ….[Optum] owned by…UnitedHealth Group…collected the medical diagnoses, tests, prescriptions, costs and socioeconomic data of 150 million Americans going back to 1993…to link patients’ medical outcomes and costs to details like their level of education, net worth, family structure and race…[and] filed a patent…to gather what people share on…Facebook and Twitter, and to link this…to the person’s clinical and payment information …. Doctors and hospitals have typically been paid based on the quantity of care [provided]…[but] moving toward paying them in lump sums for caring for a patient, or for an event, like a knee surgery…[so] can profit more when patients stay healthy …. Studies show social and economic aspects of people’s lives play an important role in [health]…[but] industry has a history of boosting profits by signing up healthy people and finding ways to avoid sick people … Affordable Care Act prohibits insurers from denying people coverage based on pre-existing health conditions or charging sick people more…[but] Trump administration is promoting short-term health plans, which do allow insurers to deny coverage to sick patients…[fail] to include enough information about which drugs a plan covers…[change] things a plan covers, or how much a patient has to pay…after a patient has enrolled…[or] exclude or limit certain types of providers from their networks — like those who have skill caring for patients with HIV or hepatitis C . …. ’ [IBM] surveys 80,000 Americans a year to assess lifestyle, attitudes and behaviors that could relate to health care…[and] analyzed together to identify social and economic factors for an area….A region with too many sick people, or with patients who don’t take care of themselves, might not be worth the risk ’God forbid you live on the wrong street…[and] get lumped in with a lot of bad things …. …. [LexisNexi] uses 442 nonmedical personal attributes to predict a person’s medical costs…[with] more than 78 billion records…including people’s cellphone numbers, criminal records, bankruptcies, property records, neighborhood safety and more…to predict patients’ health risks and costs in eight areas …. People who downsize their homes tend to have higher health care costs…[likewise] those whose parents didn’t finish high school. Patients who own more valuable homes are less likely to land back in the hospital within 30 days of their discharge….[T]he largest health actuarial firm in the world, Milliman…[uses] LexisNexis scores…[for] individual patients and make adjustments to protect themselves from losses ’No one gave anyone permission to do this…[and] not health data…[but] inferred data’ …[leading] to poor people being charged more…[and] harder for them to get the care they need….[Employers] could even decide not to hire people with…high medical costs in the future …. [Our] policymakers could…protect people’s information…[like] ’Europe, data protection is a constitutional right’….[Also] health scores should be treated like credit scores. Federal law gives people the right to know their credit scores and how they’re calculated .[If] rated by whether they listen to sad songs…or look up information about AIDS online, they should know…. … ” [LexisNexis] told me that if it had calculated my scores it would have done so on behalf of…my insurance company. So, I couldn’t have them. https://www.npr.org/sections/health-shots/2018/07/17/629441555/health-insurers-are-vacuuming-up-details-about-you-and-it-could-raise-your-rates ‘Scraper’ Bots and the Secret Internet Arms Race — “Companies are waging an invisible data war online…[using] software to scan rival websites and collect prices, a process called ‘scraping’…[with] machine-learning algorithms to help…decide how much to charge for different products…. . Google and Bing scrape web pages…for their search engines. Academics and journalists use scraping software to gather data… [ But] scraping can be a two-way street…[with] defenses to subvert scraping …. ….[ …. [One’s] showing different prices to real people than to bots ….[So some] mask bots to avoid detection…[or] appear to be coming from smartphones Users] choice: View ads or allow the app to use ‘some of your device’s resources Sometimes bots actually tell the sites they’re visiting…[but] can also lie. One technique for detecting bots is the frequency with which a visitor hits a site….Captchas can help, but…an inconvenience for legitimate users …. . [Trouble’s] is the need to allow some, but not all, bots to scrape a site If websites blocked bots entirely, they wouldn’t show up in search results. Retailers also generally want their pricing and items to appear on shopping comparison sites…. .” [Amazon] ‘prioritize humans over bots’….[Publishers] make sure advertisers are showing a site’s viewers the same ads that they show to the publishers….[Recently] Chrome extension was accused of being used to steal passwords https://www.wired.com/story/scraper-bots-and-the-secret-internet-arms-race/ DARPA Wants Your Insect-Scale Robots for a Micro-Olympics — “[Large robots] capable in some very specific situations, but…smaller, cheaper, more specialized robots is much more efficient…[especially] with data collection as opposed to manipulation…. [ …. DARPA] program called SHRIMP: SHort-Range Independent Microrobotic Platforms…goal is ‘to develop and demonstrate multi-functional micro-to-milli robotic platforms [Tech] advances in microelectromechanical systems (MEMS), additive manufacturing, piezoelectric actuators, and low-power sensors have allowed researchers to…to create the strength, dexterity, and independence of functional microrobotics platforms…. ] DARPA expects…systems that weigh less than one gram and fit into one cubic centimeter….[to . High Jump… vertically from a stationary starting position…and survivability…>5cm Long Jump… horizontally from a stationary starting position…and survivability…>5cm Weightlifting… progressively larger masses until…>10g. . Shotput_…_ >10cm @ 1g, >5cm @ 2g … Tug of War… connected to a load…> 25mN . Rock Piling… travel to, lift, and stack weights…in a minimum of two layers without human interaction…2g, 2 layers . Steeplechase… traverse the course without human interaction or recharge between each obstacle … 2 obstacles, 5m Biathlon… traverse to a series of beacon waypoints to create an open circuit without human interaction or recharge between each waypoint…2 beacons, 5m. Vertical Ascent… traverse up two surfaces, one with a shallow incline (10º) and the other with a sharp incline (80º) … 10m at 10°, 1m at 80°.” https://spectrum.ieee.org/automaton/robotics/robotics-hardware/darpa-wants-your-insect-scale-robots-for-a-micro-olympics DARPA Plans a Major Remake of U.S. Electronics — “[T]o make small groups of engineers capable of feats that would take 100 engineers to achieve today…aiming for 2025 to 2030… around chip architecture…of deep neural nets and other implementations**….** [A] program called Hive …[is] making associations across data sets which aren’t densely connected…doing things like updating memory access patterns, updating the type of cores that would be doing the processing, and working across the software stack to do a hardware/software codesign for a variety of applications…. ’…[ [Next] is something we call ‘software-defined hardware where] hardware is smart enough to reconfigure itself to be the type of hardware you want, based on an analysis of the data type that you’re working on ….[The] hard thing is…how to do that data introspection, how to reconfigure the chip on a…millisecond timescale…monitor whether you’re right…[and] constantly evolving toward the ideal solution…. … …. [Lastly] is the ‘domain specific system-on-chip starting with the software-defined radio…[then] to machine vision and machine learning and other domains to see if you can still have simplified programming models running on top of hyperspecialized hardware [Work] showed that two to three student designers can do full system-on-chip designs by abstraction and automation …. … Idea is really the intersection of machine learning and electronic design automation (EDA)…to capture the capabilities of the designer inside the EDA itself…[so] every time you use an EDA package, it gets smarter and…next design [easier] envision a cloud resource where multiple people are sharing and can all get better simultaneously…. …. [Today] rare to go to GitHub, find high-quality hardware blocks that are available, and have the verification tools and everything you would need to trust that…it is in a state that is useable for your design. Posh is…about the verification tools…[and] IP blocks that will be freely available As the abstraction of the hardware design gets higher and higher, it gets closer to the software community’s mentality…[and] a methodology to understand how good something is at a deep level before it’s used …. .” [Also] look at where memory is stored and ask: Can those same materials be used for processing information?…. Next-generation nonvolatile memory, for example, that switches very fast and with a low write energy https://spectrum.ieee.org/tech-talk/computing/hardware/darpas-planning-a-major-remake-of-us-electronics-pay-attention.html Find more of my ideas on Medium at, . A Passion to Evolve Or click the Follow button below to add me to your feed. Prefer a weekly email newsletter — free, no ads, no spam, & never sell the list — email me with “add me” in the subject line. dochuston1@gmail.com May you live long and prosper!Doc Huston

News — At The Edge — 7/28

How satellite imagery is changing every industry you know Written by Adam Kell, Comet Labs Investment Partner Watch full video of Dubai here “In 1609, Galileo wowed Venice’s big cheeses by letting them use his telescope to see ships way out at sea, a good two hours before their owners would see them enter the port. The Venetians were impressed (they doubled Galileo’s salary and gave him lifetime tenure at the University of Padua) because they immediately saw the huge financial and military advantages offered by this visionary device. A few hundred years later, we are on the cusp of an equally radical transformation in how information is gathered, analyzed and monetized. And if we pay attention, we might even save the planet.” — G. Burningham, Newsweek 2016 Learn more about Galileo’s refractor here A constellation of new startups are focused on lowering the cost and increasing the frequency of satellite images of earth. These companies include satellite builders, operators, launch companies, communications infrastructure operators, and software companies focused on drawing valuable data out of the images. In the 1990’s, when satellite imagery was first able to be sold legally, there were very few imaging satellites in orbit. These satellites were large, expensive to build, expensive to launch, bandwidth limited on how quickly they could communicate, and there wasn’t much of a market for the images themselves. With technology’s march forward in the subsequent 25 years, new things are becoming possible from a cost and data perspective that never were before. Imaging satellites Imaging satellites have sensors on them that are similar to a digital camera in your mobile phone, only with much higher-end components. The lens is different because it needs to focus on the earth’s surface 500km away, as opposed to your iPhone at arm’s distance. , focusing on different spectra of wavelengths, whereas the cell phone camera focuses on the visible spectrum. Different applications have different requirements, but there are two main variables in satellite imagery: revisit rate, or how often a certain area of earth is imaged, and spatial resolution, the size of the smallest visible feature in the image. The sensors themselves are different as well There is generally a trade-off between image resolution and temporal resolution. Higher definition images are produced from large satellites, which have larger lenses but are much more expensive to build and launch because of their size. Due to their significant cost, there are fewer of them in orbit. Fewer satellites in the constellation means less frequent coverage of land, or narrower swaths of land covered more frequently. Smaller satellites, or cubesats, , can be launched as a cluster on one rocket and are thus cheaper to build and get into orbit. The downside of cubesats are the physical geometry of the spacecraft — since the lens is smaller, the resulting images are in lower resolution. Cubesat constellations allow a higher revisit rate — in other words, you get images of the same place on earth more frequently. roughly the size of a shoebox Real-time location of the ~13,000 satellites in orbit in the year 2008 What’s changed? Every element of satellite imagery has seen significant changes in the past decade. Private companies have increasingly entered the market of building smaller satellites, such as Skybox ( ) and Planet Labs. The cost of components for these cubesats has been driven down with scale, largely due to the decreasing costs of sensors, computers, and solar cells. Launches have become much cheaper, partially from the ability to attach multiple cubesats to a single rocket. Furthermore, the launches themselves have seen more competition from private companies like SpaceX and Blue Origin, driving down cost. Satellite communication infrastructure has also seen vast improvements in the ability to . Downlink infrastructure is important both because there is an increasing number of cameras capturing images in space that contain an increasing amount of data. For example, the number of satellites in orbit has doubled since 2008, and the higher frequency resolution of a hyperspectral image might contain 20x more data compared with a panchromatic or RGB image. More satellites also create the ability to crop out cloud cover, which is a huge issue for small constellations. Because cloudy areas aren’t able to be imaged, this may greatly reduce the value of the system if the revisit rate is already low. acquired by Google downlink more data at a faster rate Finally, until recently there wasn’t a huge market for satellite imagery. Similar to many other platform technologies, now that we are starting to collect more of this data we are realizing some very interesting, valuable, and unexpected applications. Which industries are being affected? One of the first applications for satellite imagery is to count cars in parking lots of stores and restaurants as a heuristic for sales/earnings. This knowledge can be leveraged for predicting profits of a public company before their quarterly earnings are even reported. For example, after the food health issues faced by Chipotle in 2016, stock traders with access to high frequency imaging of parking lots across the thousands of Chipotle locations could have estimated the revenue hit from the bad PR. This information, updated daily, is . very powerful when making stock transactions Another application of satellite imagery is to monitor the amount of oil in tanks. Oil tanks have floating lids, and by knowing the location of the tank, the location of the sun, and the angle of the satellite, the shadow can tell you how full or empty the tank is. Like the number of restaurant/store customers, this information is extremely valuable for commodities traders who can glean some information about the reserves of oil and . how oil is moving around the world Time lapse of oil tanks at a refinery in Karachi, Pakistan Another commodity which can be monitored without much difficulty is water levels within reservoirs. Lower water levels correspond to a smaller perimeter of the water’s surface, and this can be accurately forecasted for effects on droughts, drinking and farming water. Other, more specialized sensors, like hyperspectral sensors, are being used to try to decipher the health of vegetation. This information in turn, can theoretically be used to forecast the future yield of crops like wheat, corn and soy, which valuable information to have on secondary markets. Risks and Obstacles Based on the recent explosion in funding and developments, it’s become clear that satellite imagery is here to stay. As the cost continues to decrease, and the data continues to increase in fidelity and frequency, there will be consequences that we need to be prepared to deal with. For example, groups and individuals intending to do harm will find it easier gather intelligence. Militaries will be affected, since more civilian groups will have access to information where it was historically much more limited. Another uniquely 21st century problem is the concept of space trash, which is “waste” material in Earth’s orbit that can damage valuable assets like satellites (see below). Organizations have been started, with limited success, to start to de-orbit the space trash large enough to cause damage. Beyond the painstaking task of cleaning it up, the only other viable option is to prevent the . increase of space trash in orbit ESA space debris studies: hypervelocity impact sample. The metal sheet is 18 cm in thickness, and the ball bearing 1.2 cm across, hitting at 6.8 km/s. Image Credit: ESA Interesting Startups There are a number of interesting startups working within the new ecosystem of satellite imagery. Two of the largest companies focused on are Planet Labs and (formerly Skybox Imaging, acquired by Google in 2014 for $500m). By launching cubesats the size of a shoebox (in the case of Planet Labs), or a washing machine (in the case of Terra Bella), the cost of getting satellite imagery is quickly falling. This data is also unprecedented in terms of the temporal frequency (how often a photograph of the same area of land is captured) — which is allowing fundamentally new applications. Geospatial (operator of Rapideye — a constellation of 5 satellites equipped with identical multispectral sensors and a 5m resolution) demonstrates the focus on increasing not only temporal resolution, but and as well. building and operating cubesat constellations Terra Bella Planet’s 2015 acquisition of BlackBridge spectral spatial resolutions Rapideye Satellite Constellation Several software companies are focused on building the — two of the largest are Orbital Insight and , focusing on many of the applications described in this article such as car counting and commodities monitoring. Orbital is a partner/customer of Planet’s dataset, and has productized several of the above examples, with customers focused mostly in the financial market. Several startups are working on more industry-specific applications such as using spectral analysis to . analytics stack around extracting data from this new trove of data Descartes Labs estimate mineral deposits Still other companies are working on creating a for all the new satellites that are coming on line. One of the bottlenecks for ubiquitous satellite imagery is the downlink speeds that we can use to get the data back to earth. Traditionally, NASA had used Tracking and Data Relay Satellites (TRDS), but this was designed for lower bandwidth applications. Companies like Audacy Space are focusing on creating increased connectivity between communication satellites, imaging satellites and base stations. more robust communications infrastructure A last piece of the satellite puzzle is the around getting the satellite constellations to space in the first place. One of the most well-known is SpaceX, which focuses on making reusable rockets to save cost, but several other companies are working on creating a massive reduction in the cost of getting to space. launch infrastructure Where do we go from here? Like the early days of other platforms (personal computers, internet, mobile phones), we’ve only started to scratch the surface of what can be done with satellite imagery. As the infrastructure, images, and communication networks continue to improve, the effects of this technology will ripple out to other industries, and create massive opportunities for those who position themselves to take advantage of the change. Follow us for more updates about artificial intelligence startups and technologies that are changing our world. Want to stay in touch? and we’ll give you a roundup of our favorite stories and resources for you to use every 2 weeks. Sign up for our newsletter

The New Space Race

In a landmark paper published March 29, 2024, in the journal, Entropy, a team of visionary researchers from VERSES AI has unveiled a groundbreaking framework that could pave the way for the emergence of a new form of artificial intelligence , operating on the principles of natural intelligence— one that arises from the dense interactions of networked intelligent agents, rather than from a single, monolithic system. based on a first-principles approach to multi-scale artificial intelligence The study, titled “Shared Protentions in Multi-Agent Active Inference,” represents a major milestone in VERSES AI’s ambitious roadmap towards “shared intelligence” and could have profound implications for the future of AI and human-machine cooperation. The Power of Active Inference and Shared Protentions The research, led by Mahault Albarracin and co-authored by Riddhi Jain, Toby St Clere Smithe, Daniel Friedman, Maxwell Ramstead, and renowned neuroscientist Dr. Karl Friston, pioneer of and the , draws upon insights from philosophy, biology, and mathematics to explore how shared goals and collective intelligence can emerge from the interactions of individual intelligent agents. Central to their framework is the concept of “shared protentions” — mutually attuned expectations about future states and actions that enable agents to coordinate their behaviors towards common objectives. Active Inference Free Energy Principle What are "Protentions?" The philosophical foundation of the work lies in the concept of “inner time consciousness” developed by the early 20th-century thinker Edmund Husserl. Husserl proposed that our subjective experience of the present moment always has a certain “temporal thickness” — it encompasses not just the immediate instant, but also traces of the just-past (which he called “retentions”) and anticipations of the near-future (termed “protentions”). The authors of the new study take this idea of an individual’s temporal experience and extend it to the level of a social group. They introduce the notion of “shared protentions” — the idea that members of a group can develop mutually attuned expectations about future states and actions, which then allow them to coordinate their behaviors. How Does it Work? To translate this philosophical concept into a scientific model, the researchers employ a framework from theoretical biology known as “active inference.” This approach views living organisms as continuously making inferences about the state of their environment and selecting actions that minimize surprises and uncertainty. The authors show how Husserl’s ideas can be mapped onto the components of an active inference model. Sensory inputs correspond to raw “hyletic data,” (impressions that form perceptions), while the inferred causes of those sensations make up what we perceive as our experience. Crucially, the model equips each individual with an internal representation that includes not just their own states but also those of other group members. This allows the model to capture how individuals infer each other’s mental states and anticipate their actions. Leveraging Category Theory for Unified Representation The most innovative aspect of the new framework is its integration of mathematical tools from a field known as category theory. The researchers now express how individuals make decisions using abstract math concepts known as “polynomial functors,” which represent their potential interactions and observations. They then use a technique called “sheaf theory” to stitch together the compatible parts of these individual models. This results in a unified picture of the group’s shared understanding, termed a “consensus topos” by the authors. Within this formal framework, the “shared protentions” that enable coordinated group action emerge spontaneously as a consequence of each individual’s understanding and reasoning being influenced by the need to maintain consistency with the group. In other words, the underlying alignment of expectations that allows individuals to work together towards common goals arises naturally from the mathematics of the model. An Example from Nature Think of it like a flock of birds flying together. Each bird is constantly adjusting its own movements based on what it sees the other birds doing. It doesn’t need to have a detailed plan or a leader telling it what to do — it just naturally falls into formation by following simple rules and paying attention to its neighbors. A Human Example - Alignment of Understanding and Anticipation We can also use the example of a sports team, like a basketball team, playing together on the court. Each player on the team has a mental model of the game — they understand the rules, the objectives, and the general strategy. But more importantly, they also have a sense of what their teammates are likely to do in any given situation. This understanding is built up through hours of practice and gameplay together. During a fast-paced game, there’s no time for the players to stop and discuss each play in detail. Instead, they rely on their shared understanding and anticipation of each other’s actions. The point guard, for instance, might make a split-second decision to pass the ball to a particular teammate, not because they discussed it beforehand, but because they anticipate that the teammate will be in the right position to receive the pass. This is a prime example of “shared protentions” in action. Each player’s individual actions are guided by their expectations of what their teammates will do. And these expectations are not just one-way — they’re reciprocal and self-reinforcing. The teammate anticipates the pass because they know the point guard is likely to make it, and the point guard makes the pass because they anticipate the teammate being ready for it. Over time, this interplay of expectations and actions leads to a highly coordinated style of play, where the team seems to move and think as one unit. And importantly, this coordination emerges not from any one player’s explicit instructions, but from the implicit alignment of each player’s understanding and anticipations. This is the essence of what the researchers’ mathematical model captures — It’s a powerful insight into the cognitive underpinnings of teamwork and collective action. how shared goals and coordinated action can arise naturally from the interplay of individual minds, guided by the need to maintain a coherent, mutually aligned understanding of the world. VERSES AI's Vision for Shared Intelligence The significance of this work extends far beyond the realm of academic theory. In a post on LinkedIn, Albarracin explained that the paper “sets the stage for .” This stage, which roughly corresponds to what is popularly known as “Artificial Super-Intelligence,” envisions the emergence of planetary-scale, distributed intelligences from the highly coordinated interactions of networked Intelligent Agents. The key insight of the “Shared Protentions” paper is that such collective intelligences are not just a distant dream but a natural consequence of the principles of Active Inference and the mathematical tools of category theory. VERSES’ Active Inference intelligence roadmap stage S4 of Shared Intelligence The Mathematics of Shared Intelligence To understand how this works, it’s helpful to step back and consider the basic premise of Active Inference. This framework, rooted in neuroscience and theoretical biology, views Intelligent Agents as constantly making deductions and drawing conclusions about the state of their environment and choosing to act in a way that closes the gap between expectation and reality — refining understanding to better anticipate what will happen. In the “Shared Protentions” paper, the authors show how this process of inference and action selection can be formally modeled using abstract mathematical objects called “polynomial functors” and “sheaves,” as explained above. Coordinating Intelligent Agents through Implicit Alignment By applying these tools to networks of interacting Intelligent Agents, the researchers demonstrate how individual agents can intuitively align their expectations and coordinate their behaviors, even without explicit communication. In essence, they provide a mathematical recipe for the unspoken emergence of shared goals and collective intelligence from the bottom up. The Role of HSML in Enabling Shared Intelligence But what makes this research truly groundbreaking is its integration with . HSML is a common language that enables seamless interoperability between Active Inference Intelligent Agents, humans, and the scores of devices that comprise the Internet of Things (IoT). By programming context into objects and spaces, HSML provides Active Inference Agents with real-time data about their environments, as well as the sensory inputs from IoT devices and robots. VERSES AI’s Hyperspace Modeling Language (HSML) Embedding Human Values into the Spatial Web The “Shared Protentions” paper lays the theoretical foundation for In other words, it provides a principled way to embed human values and objectives into the very fabric of the Spatial Web, ensuring that the collective intelligences that emerge from it are aligned with our goals and aspirations. translating high-level human directives, encoded in HSML, into the inherent alignments of expectations that guide the cooperative behaviors of Autonomous Intelligent Agents. The Far-Reaching Implications of VERSES AI's Research The implications of this research are staggering. As we move towards a future in which , from Smart Cities to healthcare to scientific research, the ability to create cooperative, context-aware intelligences that can seamlessly coordinate their actions in pursuit of common goals will be essential. The “Shared Protentions” paper, in conjunction with the — & , offers a roadmap for achieving this vision. Autonomous Intelligent Systems are increasingly integrated into every aspect of our lives Spatial Web Protocol HSTP HSML Challenges and Opportunities on the Path to Shared Intelligence Of course, there are still many challenges to be overcome. This robust, secure, and ethical framework, as well as the deployment of . However, the publication of this paper marks a crucial turning point in our understanding of what is possible. these technologies, will require ongoing collaboration between researchers, policymakers, and the broader public Natural Intelligence-A New Era in Artificial Intelligence As we stand at the threshold of a new era in artificial intelligence, the pioneering work of Friston, Albarracin, and their colleagues at and the offers a promising vision of future in which humans and machines can work together in previously unimaginable ways. By cracking the code of shared intelligence and providing the tools to embed the building blocks for it in the very infrastructure of our world, they are laying the foundation for a new paradigm in AI — one that operates with the same mechanics as biological intelligence, and one that could transform our society in ways we are only beginning to imagine. 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VERSES AI's Revolutionary Framework Lays Down The Path to Natural Shared Super-Intelligence

The Essential Crypto Wallet Guide for 2024: Navigating the Best in the Business In the dynamic realm of cryptocurrency, the importance of selecting the right wallet cannot be overstated. With an overwhelming array of options available, choosing a wallet—or rather, wallets—that cater to your specific needs is paramount. This guide introduces you to six indispensable wallets for 2024, each excelling in different facets of the crypto ecosystem. From securing your digital assets to optimizing your trading strategies, these wallets form the cornerstone of a well-rounded crypto toolkit. Framework for Review: Understanding Wallet Categories Before diving into our top picks, it's crucial to understand the landscape of crypto wallets. Broadly categorized into web, hardware, and multi-chain wallets, each type serves distinct purposes: Ideal for users engaging in fast-paced trading, DeFi, and other online activities requiring quick transactions. Web Wallets: Best suited for long-term storage, offering unmatched security for your cryptocurrency investments. Hardware Wallets: Cater to users who navigate across various blockchains, offering flexibility and broad asset support. Multi-Chain Wallets: Crypto Wallets to Check Out In 2024 : The Seamless, Seedless Wonder 1. Core Multi-Chain Wallet Type: Crypto investors, DeFi enthusiasts and NFT collectors Best For: Non-custodial, seedless setup, multi-chain support (including Ethereum, Avalanche, Bitcoin), and integrated portfolio tracker. Key Features: App Store Rating: Core Wallet Chrome (with Desktop, Chrome Extension, & Mobile availability) Launch Platform: Key Features: Non-custodial wallet with Ledger hardware support Sign-up via Google or Apple ID with two-factor authentication Bridge functionality across Bitcoin, Ethereum, and more Address book for blockchain contacts Fee-less transactions for sending, receiving, bridging, swapping, and buying crypto Comprehensive DeFi toolkit including built-in AVAX staking Support for 73+ Avalanche Subnets and multiple chains Technical Review User Interface and Experience sets itself apart with a simple, intuitive design that belies its powerful features. It's engineered to be 10 times faster than MetaMask, offering split-second transactions that enhance the user experience significantly. The wallet’s ease of use is evident from the seamless signup process to the fluid navigation through its diverse functionalities. Core Multi-Chain Capability and Speed One of most lauded features is its multi-chain support, facilitating a bridge between Bitcoin, Ethereum, and other blockchains directly within the wallet. This feature, combined with its rapid transaction capabilities, positions Core as a highly efficient tool for users who operate across various crypto environments. Core’s DeFi and Staking is built with DeFi enthusiasts in mind. It comes equipped with built-in AVAX staking features, offering around 8% protocol-generated yearly rewards. Additionally, the wallet provides dedicated support for Avalanche Subnets, with access to over 73 and counting, amplifying its appeal to users invested in the Avalanche ecosystem. Core Community and Ecosystem Feedback Feedback from the community and partners like Trader Joe, BENQI, HyperSpace, WooFi, YieldYak, and Dexalot underscores Core’s effectiveness and efficiency. Partners praise Core for its fast, smooth experience and its comprehensive toolkit that supports a wide range of DeFi activities including staking, swaps, and bridging. Future Outlook: Final Thoughts on Core Core represents more than just a wallet; it's a comprehensive platform that caters to the needs of modern crypto users, especially those within the Avalanche ecosystem. Its blend of speed, security, multi-chain support, and DeFi functionalities makes it an indispensable tool for anyone looking to navigate the complexities of Web3 with ease. Whether you’re staking AVAX, swapping tokens, or managing a diverse portfolio of digital assets, Core offers a streamlined and secure gateway to the world of blockchain. For users seeking a reliable, fast, and feature-rich wallet, stands out as a top contender, delivering on its promise to be a "Swiss army knife" for Avalanche users and beyond. With ongoing updates and a responsive development team, Core is poised to remain at the forefront of wallet technology, making it a wise choice for both new and experienced users in the dynamic world of cryptocurrency. Core The Expanding Multi-Chain Maven 2. Phantom: Multi-Chain Wallet Type: Users exploring beyond EVM chains Best For: Originating as a Solana wallet, now expanding to Ethereum and Bitcoin, including support for BTC20 and Ordinals. Key Features: Store Rating: Phantom App Phantom Wallet: Unveiling Bitcoin and Ordinals Support - A Technical Review Phantom wallet, a name synonymous with versatility in the cryptocurrency realm, has taken a significant leap by introducing support for Bitcoin, Ordinals, and BRC-20 tokens. This review delves into the features, usability, and innovations that Phantom brings to the table, particularly focusing on its integration of Bitcoin and Ordinals, marking a new era for users who desire a unified wallet experience across multiple blockchains. Overview Mobile, Browser Platform Compatibility: Bitcoin and Ordinals support in Beta Beta Status: Key Features: Full support for Bitcoin, Ordinals, and BRC-20 tokens Easy management of Bitcoin addresses with options for Taproot and Native SegWit Detailed transaction overviews with ETA and USD value conversions Protection for inscribed and rare sats Connected apps for browsing, buying, and listing Ordinals and BRC-20 tokens Immersive ordinals gallery and automatic spam detection Integration of Bitcoin and Ordinals Phantom's expansion to support Bitcoin and its related innovations, such as Ordinals and the BRC-20 token standard, showcases the wallet's commitment to embracing the broader crypto ecosystem. By incorporating Bitcoin, Phantom not only acknowledges the foundational role of Bitcoin in the web3 movement but also enhances its utility for users seeking a multi-chain wallet that encompasses the best of Solana, Ethereum, and Bitcoin. User Experience and Features Phantom aims to simplify the often complex world of Bitcoin and Ordinals for its users. The wallet introduces an intuitive interface for managing Bitcoin transactions, including the ability to toggle between Taproot and Native SegWit addresses, ensuring users have control over their transaction preferences and security features. The inclusion of an immersive ordinals gallery and connected apps like Magic Eden and UniSat facilitates a seamless experience for collecting and interacting with Ordinals and BRC-20 tokens. Security and Usability Enhancements With detailed transaction overviews, users gain insight into the estimated time of arrival (ETA) and balance changes for each transaction, with the added convenience of BTC to USD conversions for better context. Phantom also prioritizes the safety of unique assets like Ordinals and rare sats, implementing features to prevent their accidental expenditure. Additionally, automatic spam detection and rich Ordinals metadata further secure and enrich the user experience. Enabling Bitcoin and Ordinals Support Phantom has made enabling Bitcoin and Ordinals support straightforward, requiring users to simply toggle the Bitcoin network on in the wallet's settings. This opt-in approach respects user preferences and positions Phantom as a versatile wallet catering to diverse needs within the crypto community. Future Outlook: Final Thoughts on Phantom Wallet By offering a comprehensive platform that bridges the gap between major blockchains like Solana, Ethereum, and now Bitcoin, Phantom enhances its appeal to a wide range of crypto users, from collectors and traders to multichain enthusiasts. As the wallet progresses from its beta phase, the crypto community eagerly anticipates the full realization of Phantom's vision for a seamless, secure, and integrated digital asset experience. As Phantom continues to evolve, the wallet's roadmap includes expanding support for trusted apps and introducing Bitcoin-friendly features such as Ledger support and customizable gas fees. These forthcoming updates underscore Phantom's dedication to making cryptocurrency safe and accessible for a global audience. The Dynamic Duo 3. Trust Wallet with SWIFT: Non-Custodial Wallet Type: Navigating EVM chains with ease Best For: Smart contract wallet SWIFT integrated into Trust Wallet, support for multiple EVM chains, and innovative gas subsidies. Key Features: App Store Rating: Trust Wallet A Comprehensive Review of the Secure Multi-Chain Platform Trust Wallet: Trust Wallet has established itself as a pivotal player in the cryptocurrency wallet space, offering a wide array of features that cater to both novice and experienced users navigating the Web3 ecosystem. Launched in 2017 and trusted by over 70 million people worldwide, Trust Wallet provides a seamless and secure platform for managing a diverse range of digital assets across more than 100 blockchains. This review explores the functionalities, security measures, and user experience offered by Trust Wallet. Overview Mobile App, Browser Extension Platform Compatibility: 70M+ User Base: Independently Audited Audit Status: 10M+ assets, 600M+ NFTs across 100+ blockchains Supported Assets: Key Features Multi-Chain Support At its core, Trust Wallet is a self-custody multi-chain wallet that supports millions of assets across a spectrum of blockchains, including Bitcoin, Ethereum, Solana, Cosmos, Optimism, and many others. This extensive support ensures users can manage their cryptocurrency portfolio from a single platform, facilitating activities such as buying, selling, swapping, and earning on their digital assets. User Experience Trust Wallet emphasizes a simple and seamless user experience, offering a smooth mobile app and desktop experience with powerful tools to support users’ entire Web3 journey. Users can easily deposit crypto from exchanges like Binance and Coinbase directly into their Trust Wallet, streamlining the process of taking full control over their digital assets. Privacy and Security Privacy and security are paramount in Trust Wallet’s design. The wallet employs robust privacy measures, ensuring users remain in control of their data and digital assets without compromising on safety. Key security features include: True ownership of crypto assets, with users retaining control of their private keys and secret phrases. Encrypted Cloud Backup for enhanced wallet security. Zero personal tracking, with no collection of IP addresses or balance information. Alerts for risky transactions and dApp connections, helping users stay safe while exploring Web3. Web3 and Community Integration Trust Wallet serves as a comprehensive platform for engaging with the Web3 space, allowing users to buy, sell, swap crypto, earn rewards, manage NFTs, and discover dApps all in one place. The wallet is powered by a vibrant and diverse community, offering insights into DeFi, blockchain technology, and the importance of securing private keys. Building on Trust Trust Wallet also provides a platform for blockchain developers to build their dApps and wallets natively, connecting with millions of users without worrying about low-level implementation details. This community-centric approach fosters innovation and accessibility within the Web3 ecosystem. Future Outlook: Final Thoughts on Trust Trust Wallet stands out as a versatile and secure option for users looking to explore the vast potentials of Web3. With its multi-chain support, emphasis on security and privacy, and user-friendly interface, Trust Wallet provides a robust foundation for managing digital assets. Whether you’re a DeFi enthusiast, an NFT collector, or simply looking to secure your cryptocurrency portfolio, Trust Wallet offers a comprehensive solution tailored to meet the needs of the modern crypto user. : The Speedy Contender 4. Rabby Web Wallet Type: Advanced EVM chain users Best For: Supports up to 50 wallets without performance issues, integrated portfolio checker, and superior security features. Key Features: App Store Rating: Rabby Wallet Technical Review has emerged as a significant player in the realm of cryptocurrency wallets, particularly for users deeply entrenched in the Ethereum ecosystem and beyond. Designed to cater to a wide array of blockchains, distinguishes itself through its multi-chain capabilities, security features, and user-centric experience. This review delves into the technical aspects of Rabby Wallet, shedding light on its features, usability, and how it stands against competitors like MetaMask. Rabby Wallet Rabby Overview Chrome Extension, Desktop, Mobile (Beta) Compatibility: Key Features: Support for 141 chains including mainnets and testnets Pre-sign security checks User-friendly interface showing estimated balance changes Open source and audited by SlowMist Multiple signing modes including hardware and institutional wallets Multi-Chain Support and Usability hallmark is its smooth multi-chain experience, automatically switching to the corresponding chain based on the user's visited site. This feature not only enhances usability but also positions Rabby as a versatile wallet for users engaging with multiple blockchains. With integrated support for 141 chains, including everything from Ethereum and Arbitrum to more niche chains like Zora and zkSync Era, Rabby ensures broad accessibility and functionality for its users. Rabby's Security Security is paramount in the design of Rabby Wallet. It introduces a pre-sign check powered by Rabby's security engine, aiming to safeguard users from malicious transactions. The wallet is open-sourced and has been audited by SlowMist, providing transparency and trust in its security mechanisms. Rabby also inherits the well-proven private key management component from MetaMask, further solidifying its reliability. User Experience Rabby excels in delivering a user-friendly experience. It is the first wallet to show users their estimated balance change upon transaction completion, providing clarity and confidence in each action. Despite its focus on security, Rabby does not compromise on user experience. The wallet's interface is intuitive, making it accessible for both novices and experienced users. Additionally, Rabby is licensed under the most friendly MIT license among mainstream extension wallets, emphasizing its user-centric approach. Diverse Signing Modes Rabby supports multiple signing modes, catering to a wide range of users from casual holders to institutional investors. Hardware wallet support includes popular options like Ledger, Trezor, and BitBox02, among others. Institutional wallets such as Gnosis Safe and FireBlocks are also supported, alongside mobile wallets like MetaMask Mobile and Trust Wallet. This inclusivity ensures that users have the flexibility to secure their assets in a manner that best suits their needs. Future Outlook: Final Thoughts on Rabby Wallet Rabby Wallet stands out as a comprehensive solution for users navigating the complex landscape of multiple blockchains. Its robust security features, coupled with a user-friendly interface and extensive chain support, make it a compelling choice for a broad spectrum of crypto enthusiasts. The wallet’s open-source nature and the transparency of undergoing a security audit by SlowMist add layers of trust and reliability. Whether you're a seasoned trader looking for seamless multi-chain navigation or a newcomer seeking a secure and intuitive wallet, Rabby offers a solid foundation for engaging with the digital asset world. Building Your Crypto Wallet Arsenal Each of these wallets brings something unique to the table, addressing different aspects of the crypto experience. Whether you're trading daily on DeFi platforms, holding long-term investments, or exploring the vast landscapes of NFTs and new blockchains, integrating these tools into your crypto strategy can significantly enhance your security, efficiency, and overall success in the digital asset space. Don’t forget to like and share the story! This author is an independent contributor publishing via our brand-as-author program. Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure:

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