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Digital Technology is everywhere and it is redefining how we live, communicate, and work. Most importantly, it accelerates how we innovate. The unprecedented pace of innovation we experience is powered by a massive digital ecosystem of resources, tools, infrastructure, and advanced capabilities that a few years ago would have been classified as ‘science fiction’. Our and are impacted by recent innovations leading to new forms of communication and collaboration. Our digitized world accelerates innovation in many ways. social structures work models Movements such as the and both innovation and from it. open-source open collaboration drive benefit The following summarizes the and . the state of digital technologies, things to come, opportunities for innovation We Generate an Astronomical, Rapidly Growing Amount of Data. The world’s network of humans and machines generates astronomical volumes of data. It is estimated that our will size about by 2025 [1]. And this volume is growing exponentially. Of course, a significant percentage of this is just or even , , and data. But subsets of this data describe , and at the same time, . digital universe 175 zettabytes noise fake low-quality unreliable most types of human activity at a global scale at an amazing level of detail Along with the events coming from connected devices and the measurements from billions of sensors — this massive, growing data set forms a new type of : a vast amount of time-series of events and signals, machine states, news, opinions, research findings, discoveries, social interactions, decisions, environmental measurements and more. global memory The historians of the future will be able to look back and reproduce the planet’s activity with a granularity of seconds. The machines of the future will be able to consume and make sense of our reality in ways we cannot even imagine. Of course, there are substantial ethical questions and concerns regarding ownership and usage of this data: This question could be an excellent theme for innovation on its own as we should not rely on the political will and corporate social responsibility; regulation is only a part of the solution. Technology itself can provide excellent ways of data ownership and ethical use. how might we use, protect and leverage humanities’ accumulated data in an ethical way and for the greater good? Our Data Processing Capability is Impressive but still, Rather Limited. Current data processing technologies are capable of making sense of the vast amounts of content we produce. Sophisticated algorithms can identify in the data and generate insights that make applications and devices smart. non-obvious patterns Statistical and machine learning algorithms allow optimal, in complex situations — for example, powering autonomous cars to react in optimal ways, enabling systems to identify cyber-attacks or controlling the traffic load of a smart city. real-time decision-making Artificial Intelligence empowers computers , , [ii], and soon — to deduce new information from existing knowledge. Machines can already recognize human emotions, and they can communicate verbally at an impressive level. to see to listen to smell to infer But still, there is massive in the immense volumes of data and content we produce. The , the , and of the world’s accumulated data create the need for , , and information and insights. untapped value amount breadth depth new ways to summarize visualize present To deal with the potential of information overload, companies will soon feel the need to move and to automatically synthesized and . Corporate executives will soon interact with Business Intelligence agents providing instant answers to business questions instead of multi-page reports and worksheets. from regular reports dashboards, data stories smart insights The world needs novel methods to experience and make sense of the massive data we generate. Intelligent content synopsis, personalized insights, ‘data navigation’ systems, VR and AR experiences to visualize complex ‘data worlds’, voice-driven insights are just some examples of potential innovations in the data space. Artificial Intelligence is Getting Intelligent. Computer vision and Natural Language Processing are characteristic examples of recent advances in the field of AI. Simply put, Computer Vision is the class of algorithms that allow a computer to see — to analyze images and videos and identify entities, objects, and specific instances such as locations, persons, things — or even the situation and the particular occasion visualized in an image. Combined with other technologies such as fast networking and edge computing, Computer Vision creates opportunities for breakthrough innovations across domains, including (autonomous cars, self-organizing fleets, navigation systems, and smart cities), (diagnosis), and more. transportation medical systems robotics At the same time, Language Understanding is making tremendous progress — making more intelligent, contextual, and proactive. Your smart speaker will soon perform in a , able to instead of just responding to an isolated question. digital assistants conversational mode drive meaningful dialogues Digital assistants of the future will know by analyzing the voice in real-time, and thus, they will be able to respond in personalized ways — . By leveraging accumulated knowledge about the user, conversational experiences will become more personal, useful, and relevant for the , the , and the . who they are discussing with matching the communication style and information needs of each specific user particular user moment in time estimated mood AI-powered is becoming more accurate and faster — recent advances allow while and other voice attributes of the original speaker. translation speech to speech translation maintaining the tone of voice With the help of Artificial Intelligence, — hence the term . People are already interacting naturally with smart devices — we can control simple functions of our home via our smart speaker or digital assistant or use voice commands to perform a web search and manage our calendar. Soon, we will be able to use not only voice but also — a technology recreating the sense of touch by applying force feedback, vibrations, or motions to the user. communication with machines is becoming seamless Natural User Interfaces haptic interfaces Our Reality Gets Augmented. Technology is not only changing how we interact with our intelligent machines but also . Typically delivered through smart glasses, (also known as or ) provides an extra layer of information relevant to the particular object a user is looking at or interacting with. It is what we get when physical and digital worlds blend into a single experience. how we see and understand the world Augmented Reality extended mixed reality This area will grow rapidly — the space for innovation is unlimited: New , , and , , for field workers — are just some examples of the applications that are on the way and are about to change the ways we understand the world. content experiences data exploration visualization techniques dynamic mapping of the physical world industrial applications Analogous progress and opportunity for innovation exist for — which allows new digital worlds to be created and helps e.g. join a human activity happening elsewhere. Virtual Reality experience remote environments or situations Content creation and new experiences for VR/AR defines a great new stage for innovations across multiple domains and business scenarios, including e-commerce, gaming, social applications, learning and education, and healthcare. Humanity’s Memory Becomes Persistent. Another significant advance is in digital tech is the (DLTs) such as the . Such systems are based on an extensive network of nodes, each running on a different machine and maintaining a complete copy of a database of transactions. Nodes communicate with each other on a peer-to-peer fashion — with no single entity or authority controlling the system. A process of and makes these systems and — they are not controlled by specific entities, and they don’t require trust between transaction participants. Distributed Ledger Technologies Blockchain transaction verification voting among the nodes trustless decentralized Blockchain is considered to be one of the most disruptive technologies of our times. It is already powering cryptocurrencies, and it is expected to drive massive transformation in social, government, and financial sectors — as the solution for distributed, decentralized, and of data or code (smart contracts). immutable storage Robots are Finally Getting Smart. Either purpose-specific or general-purpose, robots are already here in various forms. The discipline of Robotics combines multiple technologies, including sophisticated hardware, advanced software systems, and AI algorithms, to develop smarter, robots that can perform a widening range of tasks. autonomous Robots are powered by advanced Artificial Intelligence and take advantage of the fast connectivity and edge computing, to perform complex . Robots may come in multiple form factors — , , , , and so on. New generations of robots are connected — they take advantage of the world’s knowledge and digital infrastructure to become smarter and more adaptive. In the near future, general-purpose robots will become truly proactive and autonomous with advanced and the ability to recognize complex situations and act accordingly. They will have a ‘personality’, individual communication styles, and strategies. cognitive tasks in real-time humanoids nano-robots military industrial context understanding Biotechnology Redefines Life. At the same time, advances in , are driving massive changes across industries, from medical and pharmaceutical to agriculture and food engineering. Research in presents significant progress — recent announcements of quantum supremacy demonstrate how this new class of systems outperforms the most powerful computing systems we currently have. biotechnology bio-engineering, and bioinformatics Quantum Computing The years to come will bring impressive technological breakthroughs with a massive impact on our lives, markets, and societies. In our connected world, with the unprecedented level of , , and , , at scale, and in several forms. It may be driven by corporations, secret research labs, and universities but also from , , or simply by thousands of across the globe. information knowledge ideas exchange innovation is happening continuously startups individual scientists creative individuals [1] Originally published in https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf The Innovation Mode Blog Cover image by Prawny from Pixabay

Innovation Opportunities in Data, AI, AR, Robots, Biotech, More [Overview]

It’s been an exciting, but complex year in the data world. Just as , the data tech ecosystem has continued to “fire on all cylinders”. If nothing else, data is probably even more front and center in 2018, in both business and personal conversations. Some of the reasons, however, have changed. last year On the one hand, data technologies (Big Data, data science, machine learning, AI) continue their march forward, becoming ever more efficient, and also more widely adopted in businesses around the world. It is no accident that one of the key themes in the corporate world in 2018 so far has been “ ”. The term may feel quaint to some (“isn’t that what’s been happening for the last 25 years?”), but it reflects that many of the more traditional industries and companies are now fully engaged into their journey to become truly data-driven. digital transformation On the other hand, a much broader cross-section of the public has become aware of the pitfalls of data. Whether it is through the very public debate over the , the Cambridge Analytica scandal, the massive Equifax data breach, GDPR-related privacy discussions or reports of growing , the data world has started revealing some risks of AI government surveillance in China darker, scarier undertones. Both are the flipside of the same phenomenon, which has been brewing for many years but is now in full display: just about everything (whether personal or professional) is rapidly getting digitized, and data technologies are becoming more adept than ever at processing and analyzing this massive data exhaust, increasingly in real time. From this can result . The debate on how to combine this great power with a necessary sense of responsibility has become essential. both magic and abuse Let’s highlight some of the key trends and events of 2018. Infrastructure & Analytics From an industry standpoint, the data ecosystem remains as exciting and vibrant as ever, with a rich tapestry of innovative startups, mature “scale-ups”, and many aggressive public technology vendors. Most importantly, many customers large and small are those technologies , and reaping undeniable value from their efforts. deploying in production at scale As the cycle of replacing older IT technologies with more modern data products continues, it seems that the Big Data market (infrastructure, analytics) is cycling through the early majority of buyers and transitioning into the late majority of the traditional adoption curve. In addition, the data world continues its inexorable evolution towards the cloud. It is actually staggering to see how fast the large public cloud providers (AWS, Azure, Google Cloud Platform, IBM) are growing, considering they already each generate billions of dollars of revenues every quarter. The trend raises ongoing concerns around , and this may open up opportunities for startups offering solutions. However, to date even companies adopting multi-cloud strategies tend to still rely on one vendor as their primary provider. vendor lock-in multi-cloud As they keep growing, large cloud providers increasingly compete with each other by offering a wide array of Big Data, data engineering and machine learning tools through their platforms (e.g., Amazon Neptune, Google AutoML, etc.) — and often with aggressive pricing, to attract more developers, as their true business model is data storage. As the scope and sophistication of such tools keep growing, this has a big impact on the data technology landscape, making it arguably , at least for broad, horizontal opportunities. A bit more every year, the list of product announcements at big annual cloud vendor conferences (see AWS , for example) sends shockwaves in the startup industry, as they put cloud vendors in direct competition with dozens of VC-backed startups in one fell swoop. It will be interesting to see how public markets react to the upcoming Elastic IPO, an open-source software company that saw Amazon launch a direct competitor, Elasticsearch, three years ago. harder for startups to compete re:Invent Plenty of opportunities for startups remain, however, as long as they are sufficiently differentiated. Many in the space are scaling fast, and there are a number of particularly interesting, fast-growing segments in the infrastructure and analytics part of the ecosystem, including /real-time, , and . The explosion of interest in AI has also led to great opportunities (and a lot of funding) in , , tools, and platforms enabling the streaming data governance data fabrics/virtualization AI chips GPU databases AI devops deployment of data science and machine learning in the enterprise. Machine Learning & AI It’s certainly been a , with anything from the prowess of AlphaZero to the staggering pace of release of new advances — new forms of Generative Adversarial Networks, Vicarious’ new Recursive Cortical Networks, Geoff Hinton’s new Capsule Networks. AI conferences like NIPS have grown to attract 8,000 people and thousands of academic papers are being submitted every day. wild year in the world of AI research At the same time, the pursuit of , perhaps thankfully so. Much of the current wave of excitement (and fear) about AI results from the impressive performance of deep learning since 2012 but, in the AI research community, there’s a as some question the foundations of deep learning (backpropagation) and others look to move past what they consider “brute force” approaches (lots of data, lots of computing power), perhaps in favor of more neuroscience-based approaches. AGI remains elusive growing sense of “what now?” Far from fearing robot world domination, many in the AI research community are concerned that continued over-hyping of the field may eventually disappoint and lead to another AI nuclear winter. Outside of AI research, however, we are just at the beginning of a wave of deployment and application of deep learning in the real world across a variety of problems involving speech recognition, image classification, object recognition and language, in different industries. If the infrastructure and analytics part of the ecosystem is getting to the late majority, we’re still very much in early adopter territory for enterprise and vertical AI applications. The that started a year or two ago has mostly continued unabated, even though the AI startup market is (arguably) showing signs of finally cooling down. Expectations, round sizes and valuations remain high, but we are certainly past the phase where big Internet companies would snap up very early AI startups at high prices just for the talent. The air is also clearing up a bit and revealing “real” AI startups, versus a number of other companies that were leveraging the hype. Some of the AI startups that were founded in the 2014–2016 time frame are starting to hit early scale, and many are offering increasingly interesting products including health, finance, “industry 4.0” and back office automation. Deep learning will continue bringing a lot of value in real world applications for years to come, and vertical-focused AI startups have many great opportunities ahead of them. Cambrian explosion of deep-learning based startups across industries and verticals This continued explosion is very much a global phenomenon, with Canada, France, Germany, the U.K. and Israel being particularly active. However, , with reports of government-led pooling of data at mind-boggling scale (across Internet companies and municipalities), rapid advances in areas such as facial recognition and AI chips, and gigantic rounds of financing for its startups: according to CB Insights, China accounted for only 9% of global AI deal share but nearly 48% of global AI funding in 2017, up from 11% in 2016 (see some examples below). China seems to be playing at a completely different level in AI In the same vein, (and ownership and security) are emerging as a major concern around the world. In the early days of the Internet, data privacy was about protecting what we did online, a comparatively small portion of our activities. Correspondingly, only a small (albeit vocal and passionate) minority of people truly cared. As just about every aspect of our personal and professional lives is now connected to the Internet through an ever increasing array of connected devices, the stakes are changing. With its ability to spot anomalies in massive data sets, predict outcomes and recognize faces, issues of data privacy AI is compounding the data privacy problem. A separate but related concern is that a lot of this data is owned by large Internet companies (GAFA). Some, like Facebook, have proven to be a less than perfect steward of it. Nonetheless, this data provides them an unfair advantage in the race to produce ever more powerful AI. Against those issues, an emerging theme is to think of the , as well as a way for others, outside of GAFA, to produce great AI. Crypto economics are viewed as a way to incentivize individuals to provide their personal data and for machine learning engineers to build models by processing this data anonymously. It all remains very experimental, but some early marketplaces and networks are emerging blockchain as a possible foil against the risks of AI The 2018 Landscape Without further ado, here’s our 2018 landscape. Quite semantic note: buzz terms come and go. Fewer people speak about “Big Data”, many more about “AI”, often to described the same reality. Consequently, we have slightly rebranded our 2018 landscape: it is now called the “Big Data & AI” landscape! To see the landscape at full size, . click here (The image is high-res and should lend itself to zooming in well, including on mobile) To download the full-size image, . click here To view a full list of companies in spreadsheet format, . click here This year, my FirstMark colleague provided immense help with the landscape. Demi Obayomi We’ve detailed some of our methodology in the notes to this post. Thoughts and suggestions welcome — please use the comment section to this post. Who’s in, who’s out On the exit front, the last year (since our 2017 landscape) has seen solid, but not extraordinarily strong. A few key companies appearing on the landscape went public, in particular Cloudera, MongoDB Pivotal and Zuora. Others are preparing to go out at the time of this writing, such as Elastic. Some notable acquisitions also occurred, including in particular Mulesoft (acquired by Salesforce post-IPO, for $6.5B), Flatiron Health (acquired by Roched for $2.1B), Appnexus (acquired by AT&T for $1.6B), Syncsort and Vision Solutions (acquired for $1.2B by Centerbridge Partners), Moat (acquired by Oracle for $850M), Integral Ad Science (acquired by Vista Equity Partners for $850M), eVestment (acquired by NASDAQ for $705M) and Kensho (acquired by S&P Global for $550M). It is worth noting that, other than Mulesoft, all those companies are headquartered on the East Coast (New York, Boston and Atlanta). Many other companies were also acquired for smaller amounts: Gigya (SAP), Blue River Technology (Deere & Co), CoreOS (Red Hat), Guavus (Thales), Lattice Data (Apple), Socrata (Tyler Technologies) and PracticeFusion (AllScripts). On the investment front, this was a year of big financing rounds for some Big Data and AI startups, particularly in China, with a number of oversized investments including Bytedance ($3B in total across 2 rounds in 2017), NIO ($1.6B across two rounds in 2017), and SenseTime ($850M across two around in 2017 and 2018). Major rounds of US companies appearing on the landscape include Snowflake Computing ($263M Series A — see our recent at ), Cohesity ($250M Series D), Dataminr ($221M Series E), Affirm ($200M Series E), Rubrik ($180M Series D), Qualtrics ($180M Series C — see an older but still relevant at Data Driven NYC), Tanium ($180M private equity round), ThoughtSpot ($145M Series D) and Coveo ($100M private equity round) and C3IoT ($100M Series F). fireside chat Data Driven NYC fireside chat ____________________ NOTES: As every year, we couldn’t possibly fit all companies we wanted on the chart. While the general philosophy of the chart is to be as inclusive as possible, we ended up having to be somewhat selective. Our methodology is certainly imperfect, but in a nutshell, here are the main criteria: Everything being equal, we gave priority to companies that have reached some level of market significance. This is a reasonably easy exercise for large tech companies. For growing startups, considering the limited amounts of data available, we often used venture capital financings as a proxy for underlying market traction (again, probably imperfect). So everything else being equal, we tend to feature startups that have raised larger amounts, typically Series A and beyond. Occasionally, we made editorial decisions to include earlier stage startups when we thought they were particularly interesting. On the application front, we gave priority to companies that explicitly leverage Big Data, machine learning and AI as a key component or differentiator of their offering. As discussed in the piece, it is a tricky exercise at a time when companies are increasingly crafting their marketing around an AI message, but we did our best. This year as in previous years, we removed a number of companies. One key reason for removal is that the company was acquired, and not run by the acquirer as an independent company.. In some select cases, we left the acquired company as is in the chart when we felt that the brand would be preserved as a reasonably separate offering from that of the acquiring company. As always, it is inevitable that we inadvertently missed some great companies in the process of putting this chart together. Did we miss yours? Feel free to add thoughts and suggestions in the comments. The chart is in png format, which should preserve overall quality when zooming, including on mobile. As we get a lot of requests every year: feel free to use the chart in books, conferences, presentations, etc — two obvious asks: (i) do not alter/edit the chart and (ii) please provide clear attribution (Matt Turck, Demi Obayomi and FirstMark Capital). Disclaimer: I’m an investor through FirstMark in a number of companies mentioned on this Big Data Landscape, specifically: ActionIQ, Cockroach Labs, Dataiku, Frame.ai, Helium, HyperScience, Kinsa, Timber, Sense360 and x.ai. Other FirstMark portfolio companies mentioned on this chart include Bluecore, Engagio, HowGood, Payoff, Knewton, Insikt, Optimus Ride, and Tubular. I’m a small personal shareholder in Datadog.

Great Power, Great Responsibility: The 2018 Big Data & AI Landscape

Hiring new figures to lead the data revolution It has been said that this new wave of exponential technologies will threaten a lot of jobs, both blue and white-collar ones. But if from one hand many roles will disappear, from the other hand in the very short-term we are observing new people coming out from the crowd to lead this revolution and set the pace. These are the people who really understand both the technicalities of the problems as well as have a clear view of the business implications of the new technologies and can easily plan how to embed those new capabilities in enterprise contexts. Hence, I am going to briefly present three of them, i.e., the , the and the . Sad to be said, I never heard about a ‘ ’, but for some strange reasons, the role is usually called either ‘ ’ or (as if data scientist won’t deserve someone at C-level to lead their efforts). Chief Data Officer (CDO) Chief Artificial Intelligence Officer (CAIO) Chief Robotics Officer (CRO) Chief of Data Science Head of Data Science ‘Chief Analytics Officer’ Let’s see then who they are and what they would be useful for. I. The Chief Data Officer (CDO) A slide taken from one of the speakers at the illustrating business drivers and capabilities and how they related to the CDO job. CDO Summit in London Apparently, it is a new role born in a lighter form straight after the financial crisis springing from the need to have a central figure to deal with technology, regulation and reporting. Therefore, the CDO is basically the guy who acts as a (tech guy) (data guy) and takes care of data quality and data management. liaison between the CTO and the CAO/Head of Data Science Actually, its final goal is . to guarantee that everyone can get access to the right data in virtually no time In that sense, a CDO is the guy in charge of ‘democratizing data’ within the company. It is not a static role, and it evolved from simply being a to being a , with the tasks of defining data management policies and business priorities, shaping not only the data strategy, but also the frameworks, procedures, and tools. In other words, he is a kind of ‘ ’ (if we agree on the distinctions between ). facilitator data governor Chief of Data Engineers data scientists, who actually deal with modeling, and data engineers, who deal with data preparation and data flow “The difference between a CIO and CDO (apart from the words data and information…) is best described using the bucket and water analogy. The CIO is responsible for the bucket, ensuring that it is complete without any holes in it, the bucket is the right size with just a little bit of spare room but not too much and its all in a safe place. The CDO is responsible for the liquid you put in the bucket, ensuring that it is the right liquid, the right amount and that’s not contaminated. The CDO is also responsible for what happens to the liquid, and making the clean vital liquid is available for the business to slake its thirst.” (Caroline Carruthers, Chief Data Officer Network Rail, and Peter Jackson, Head of Data Southern Water) I don’t want to get into what a Chief Information Officer does and how he differs from a CDO, a CTO, a CRO, or any other roles, but if you want to know more I highly recommend ’s free ebook ( ). Julie Steele see here Interestingly enough, the role of the CDO as we described it is both and . It spans indeed across the entire organization even though the CDO still needs to report to someone else in the organizational chart. Who the CDO reports to will be largely determined by the organization he is operating in. Furthermore, it is also relevant to highlight that a CDO can be found more likely in larger organizations rather than small startups. The latter type is indeed usually set up to be data-driven (with a ) and therefore the CDO function is already embedded in the role who designs the technological infrastructure/data pipeline. vertical horizontal forward-looking approach It is also true that not every company has a CDO, so how do you decide to eventually get one? Well, simply out of internal necessity, strict incoming regulation, and because all your business intelligence projects are failing because of data issues. If you have any of these problems, you might need someone who pushes the “ ” principle as the data approach to be adopted throughout the entire organization, who considers data as a company asset and wants to set the fundamentals to allow fast trial and error experimentations. And above all, someone . fail-fast who is centrally liable and accountable for anything about data A CDO is then the end-to-end data workflow responsible and it oversees the entire data value chain. Finally, if the CDO will do his job in a proper way, you’ll be able to see two different outcomes: first of all, the board will stop asking for quality data and will have clear in mind what every team is doing. Second, and most important, a good CDO aims to create an organization where a CDO has no reasons to exist. It is counterintuitive, but basically, a CDO will do a great job when the company won’t need a CDO anymore because . every line of business will be responsible and liable for their own data A good CDO aims to create an organization where a CDO has no reasons to exist. In order to reach his final goal, he needs to prove from the beginning that not investing in higher data quality and frictionless data transfer might be a source of inefficiency in business operations, resulting in non-optimized IT operations and making compliance as well as analytics much less effective. II. The Chief Artificial Intelligence Officer (CAIO) Image Credit: pexels.com If the CDO is somehow an already consolidated role, the CAIO is nothing more than a mere industry hypothesis (not sure I have seen one yet, although the strong ongoing discussions between AI experts and sector players — see and for two opposite views on the topic). Moreover, the creation of this new role highlights the emergence of two different schools of thought of enterprise AI, i.e., , and a clear cost-benefit analysis to understand which approach will work better is still missing. here here centralized vs decentralized AI implementation My two cents are that elevating AI to be represented at the board level means to really become an AI-driven company and embed AI into every product and process within your organization — and I bet not everyone is ready for that. So, let’s try to sketch at a glance the most common themes to consider when talking about a CAIO: ( : a CAIO is someone who should be able to connect the dots and (this is ’s view, by the way). If you also want to have a deeper look at what a CAIO job description would look like, the article by ; Responsibilities what he does) apply AI across data and functional silos Andrew Ng check out here Tarun Gangwani ( ): you only need to do it if you understand that and business processes; Relevance should you hire a CAIO? AI is no longer a competitive advantage to your business but rather a part of your core product ( ): first and more important, a CAIO has to be a ‘guiding light’ within the AI community because he will be one of your decisive assets . This means that he needs to be highly respected and trusted, which is something that comes only with a strong understanding of . Finally, being a cross-function activity, he needs to have the right balance between and (he needs to support different lines of business); Skills how do you pick the right guy? to win the AI talent war foundational technologies and data infrastructure willingness to risk and experiment to foster innovation attention to product and company needs ( ): there are two main risks, which are i) the misalignment between technology and business focus (you tend to put more attention on technology rather than business needs), and ii) every problem will be tackled with AI tools, which might not be that efficient (this type of guys are super trained and will be highly paid, so it is natural they will try to apply AI to everything). Risks is a smart move hiring a CAIO? Where do I stand on that? Well, my view is that a CAIO is something which makes sense, . It is an essential position to allow a smooth transition for companies who strive for becoming AI-driven firms, but I don’t see the role to be any different from what a smart tech CEO of the future should do (of course, supported by the right lower management team). However, for the next decade having a centralized function with the task of using AI (50% of the time) (50% of the time) it sounds extremely appealing to me. even though only temporarily to support the business lines and foster innovation internally In spite of all the predictions I can make, the reality is that the relevance of a CAIO will be determined by how we will end up approaching AI, i.e., whether it will be eventually considered a mere instrument or rather a proper business unit ( AI-as-a-tool) ( AI-as-a-function) . III. The Chief Robotics Officer (CRO) Image Credit: Jackie Niam/Shutterstock We moved from the CDO role, which has been around for a few years now, to the CAIO one, which is close to being embedded in organizational charts. But the Chief Robotics Officer is a completely different story. Even if someone is speaking about the importance of it (check out this if you like), it is really not clear what his tasks would be and what kind of benefits would bring to a company, and envisaging this role requires a huge leap of imagination and optimism about the future of work (and business). report In few words, what a CRO will be supposed to take care of is . To use Gartner’s words, ‘ ’. He will be responsible of the overall automatization of workflows and to integrate them smoothly into the normal design process and daily activities. managing the automated workforce of the company he will oversee the blending of human and robotic workers I am not sure I get the importance of this holistic approach to enterprise automation, although I recognize the relevance of having a central figure who will actively keep track and communicate to employees all the changes made in transforming a manual activity/process into an automated one. Another interesting point is who the CRO will report to, which is of course shaped by his real functions and goals. If robotics is deeply routed into the company and allows to create or access new markets, . If his goal is instead to automatize internal processes to achieve a higher efficiency, or to a strategic CxO (varying on industry and vertical). a CRO might directly report to the CEO he will likely report to the COO My hypothesis is that this is going to be a (and not a technical one, as you might infer from the name) which, as the CAIO, might have a positive impact in the short term ( ) but no reason to exist in the longer term. It is easier to think about it in physical product industries rather than digital products or services companies, but automation will likely happen in a faster way in the latter, so we will end up having a (to manage the supply chain workflow) as well as a (to manage instead the automation of processes and activities). strategic role especially in managing the costs of adopting early robotics technologies Chief of Physical Robotics Officer Chief of Digital Robotics Officer There is any other new emerging role you have seen in the space? If so, which is this new role and what functions/tasks does it entail? Curious to know more if something is happening below the media radars or if we need to think about something different! — — Follow me on Medium Look at my other articles on AI and Machine Learning: Unsupervised Investments (II): A Guide to AI Accelerators and Incubators A Brief History of AI Open Source in Artificial Intelligence

The new CxO gang: data, AI, and robotics

Win by Eating Their Own Dogs’ Food: How 83 Venture Capital Firms Use Data, AI & Proprietary…

**KYOTO, Japan, May 13th, 2024/Chainwire/--**The IVS KYOTO Executive Committee is delighted to announce it will host one of the largest and most celebrated annual crypto conferences in Japan in the coming weeks. The three-day IVS Crypto 2024 KYOTO event will be held at the Kyoto Pulse Plaza alongside this year’s Japan Blockchain Week Summit, from Thursday, July 4 to Saturday until July 6, 2024. The previous edition of IVS Kyoto stood out as the largest crypto event on Japan’s 2023 calendar, acclaimed for delivering a multifaceted and exhilarating experience that drew more than 10,500 attendees, 300 speakers and over 150 side events under the theme of “What’s your new adventures”. In the wake of last year’s success, the theme for IVS Crypto 2024 KYOTO is centered on the concept of “Cross the Boundaries”. Attendees, exhibitors and speakers alike, from both Japan and around the world, are asked to focus on the evolution and application of blockchain technology and explore the future of Web 3.0 through games, entertainment, AI, and more. The event will run simultaneously alongside the highly anticipated Japan Blockchain Week Summit, and this year’s program promises to be even more comprehensive than before, with a record-breaking number of blockchain and Web 3.0 pioneers present. Japan Blockchain Week 2024 will play host to events staged all over Japan, and is expected to attract more than 50,000 attendees in all. Transcending The Barrier Between Web 3.0 & Reality At Kyoto Pulse Plaza IVS Crypto 2024 KYOTO will span four entire floors at the Kyoto Pulse Plaza, with the 1st Floor given over to exhibits designed to promote the practical application of blockchain technology, with visitors able to explore how Web 3.0 is already being integrated into our daily lives. Visitors will be able to experience sessions dissecting themes such as “Blockchain Data & AI”, “SocialFi & Entertainment”, “Game-Specific Chains & Gaming Industry”, and “DeFi and Financial Efficiency”, among many others. Headline speakers gracing the stage on the first floor include Mo Shaikh (CEO and Co-Founder of Aptos Labs), Sebastien Borget (Co-founder of the  Sandbox), Joichi Ito (President of Chiba Institute of Technology), Mai Fujimoto (Co-founder of  INTMAX ), Genki Oda (Representative Director of JVCEA), Hidekazu Kondo (CEO of Japan  Open Chain), Waka Itagaki (Deputy Director of Ministry of Economy, Trade and Industry), Ken  Kanetomo (web3 Division Manager of Konami Digital Entertainment), and Hideto Kawasaki  (Director-General of web3PT of Liberal Democratic Party. The floor will be populated by the booths of dozens of cutting-edge blockchain companies, intersected by seven exclusive experience zones, with each one designed to introduce visitors to Web 3.0 from a totally different perspective. These include The Web3 Entertainment Zone, organized by SHAKE Entertainment and YGG Japan, which will showcase how the gaming industry is embracing Web 3.0. Another highlight will be the Crypto Village powered by MURA and run by Shinsekai Technologies, which is set to host a range of side events based on various themes held at different times of the day, providing a dynamic environment for meetups and communication. Inamori Hall on the 3rd Floor at Kyoto Pulse Plaza will be given over to a series of projects that bring together innovative ideas and projects in an effort to match creators and developers who aim to drive the future of Web 3.0. The projects include the eagerly-awaited AI & Web 3.0 Animation Contest, which will see young creators compete against one another to create short animations managed by blockchain, using AI and the Unreal Engine, plus tools supplied by Animechain.ai. WaveHack Global Demo Day is another highlight, with the winning hackathon teams set to win prizes totaling $500,000 and the opportunity to present their Web 3.0 projects at future events such as EDCON and WebX. Finally, the 2nd and 5th Floors are exclusive zones that will provide an opportunity for entrepreneurs and innovators to meet and share their vision with some of the most renowned venture capital investors in the crypto industry. Japan Blockchain Week 2024: A Spectacular Series Of Web 3.0 Events Japan Blockchain Week Summit is the new name for the annual Non Fungible Tokyo event that was first held back in 2018, and it is expanding to become one of the top crypto events on the planet, with more than 50,000 attendees due to show up at this year’s revamped edition. The event will run for two days within IVS Crypto 2024 KYOTO, co-hosted by JapanBlockchainWeek and N.Avenue, the operator of CoinDesk JAPAN. As the showcase event at IVS Crypto 2024 KYOTO, Japan Blockchain Week Summit will kick off this year’s Japan Blockchain Week 2024, which is set to run from July 4 to July 31 and will see multiple experiences popping up at locations all over the country. Some of the most eagerly anticipated events include "Web3 Future 2024”, which will take place on July 16, hosted by GInco Inc., and “DCENTRAL Tokyo 2024”, a three-day event that’s set to run from July 17 to July 19. Moreover, De University of Ethereum will host the "EDCON TOKYO 2024" event from July 26 to 30, with IVS Crypto/JBW Summit attendees receiving a ticket that includes a number of special perks. Last year’s IVS Crypto was a spectacular success, with more than 150 side events taking place at Kyoto’s famed Nijo Castle, Yasaka Shrine and Heian Shrine. This year’s edition is sure to be even more exciting, with over 300 events planned to take place across Japan, and the IVS KYOTO Executive Committee is delighted to reveal that it’s now looking for additional event organizers to expand what will surely be one of the most monumental shindigs in the history of Web 3.0. Those interested in participating can visit this link to find out more: https://www.notion.so/headlineasia/IVS2024-SIDE-EVENT-Guide-5903e36440cf474f8e13373d81d4211d. IVS Crypto 2024 is made possible by numerous partnerships and sponsorships with some of the biggest names in Japan’s Web 3.0 industry. Platinum partners Aptos and Animechain.ai, will be joined by a host of Gold partners, including Oasys, double jump.tokyo, Avalanche, Alibaba Cloud,  Japan Open Chain, SBI Holdings, LINE NEXT/DOSI/kaia, and Vyvo Smart Chain, as they work together to build the next generation of the (decentralized) internet. Companies and organizations interested in sponsoring can check details and make inquiries through a dedicated form on the official website. For other partners, please use our dedicated partner application form. Sponsorship inquiry form: https://www.ivs.events/about-sponsorship. Media partner, community partner, and VC partner guidebook: https://www.notion.so/headlineasia/English-Guidance-for-Partners-of-IVS2024-26c7790de96045ba9645f68672601561. For discounted tickets visit: https://www.ivs.events/crypto. Coupon code: MarketAcross About the IVS KYOTO Executive Committee Headline Japan, Inc. was established with Kyoto Prefecture and Kyoto City for the purpose of  further developing the startup ecosystem and promoting the local industry through IVS in Kyoto.  We will promote the fusion of startups with Kyoto's corporate, university, research, and cultural  resources, leading to the creation of new industries and the emergence of startups that can  compete on a global scale. Contact Fukaya, Kurita, Togawa & Yoshida ivs-pr@vectorinc.co.jp +81 3-5572-6063 This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. **KYOTO, Japan, May 13th, 2024/Chainwire/--**The IVS KYOTO Executive Committee is delighted to announce it will host one of the largest and most celebrated annual crypto conferences in Japan in the coming weeks. The three-day IVS Crypto 2024 KYOTO event will be held at the Kyoto Pulse Plaza alongside this year’s Japan Blockchain Week Summit, from Thursday, July 4 to Saturday until July 6, 2024. IVS Crypto 2024 KYOTO IVS Crypto 2024 KYOTO The previous edition of IVS Kyoto stood out as the largest crypto event on Japan’s 2023 calendar, acclaimed for delivering a multifaceted and exhilarating experience that drew more than 10,500 attendees, 300 speakers and over 150 side events under the theme of “What’s your new adventures”. In the wake of last year’s success, the theme for IVS Crypto 2024 KYOTO is centered on the concept of “Cross the Boundaries”. Attendees, exhibitors and speakers alike, from both Japan and around the world, are asked to focus on the evolution and application of blockchain technology and explore the future of Web 3.0 through games, entertainment, AI, and more. The event will run simultaneously alongside the highly anticipated Japan Blockchain Week Summit, and this year’s program promises to be even more comprehensive than before, with a record-breaking number of blockchain and Web 3.0 pioneers present. Japan Blockchain Week 2024 will play host to events staged all over Japan, and is expected to attract more than 50,000 attendees in all. Transcending The Barrier Between Web 3.0 & Reality At Kyoto Pulse Plaza IVS Crypto 2024 KYOTO will span four entire floors at the Kyoto Pulse Plaza, with the 1st Floor given over to exhibits designed to promote the practical application of blockchain technology, with visitors able to explore how Web 3.0 is already being integrated into our daily lives. Visitors will be able to experience sessions dissecting themes such as “Blockchain Data & AI”, “SocialFi & Entertainment”, “Game-Specific Chains & Gaming Industry”, and “DeFi and Financial Efficiency”, among many others. Headline speakers gracing the stage on the first floor include Mo Shaikh (CEO and Co-Founder of Aptos Labs), Sebastien Borget (Co-founder of the  Sandbox), Joichi Ito (President of Chiba Institute of Technology), Mai Fujimoto (Co-founder of  INTMAX ), Genki Oda (Representative Director of JVCEA), Hidekazu Kondo (CEO of Japan  Open Chain), Waka Itagaki (Deputy Director of Ministry of Economy, Trade and Industry), Ken  Kanetomo (web3 Division Manager of Konami Digital Entertainment), and Hideto Kawasaki  (Director-General of web3PT of Liberal Democratic Party. The floor will be populated by the booths of dozens of cutting-edge blockchain companies, intersected by seven exclusive experience zones, with each one designed to introduce visitors to Web 3.0 from a totally different perspective. These include The Web3 Entertainment Zone, organized by SHAKE Entertainment and YGG Japan, which will showcase how the gaming industry is embracing Web 3.0. Another highlight will be the Crypto Village powered by MURA and run by Shinsekai Technologies, which is set to host a range of side events based on various themes held at different times of the day, providing a dynamic environment for meetups and communication. Inamori Hall on the 3rd Floor at Kyoto Pulse Plaza will be given over to a series of projects that bring together innovative ideas and projects in an effort to match creators and developers who aim to drive the future of Web 3.0. The projects include the eagerly-awaited AI & Web 3.0 Animation Contest, which will see young creators compete against one another to create short animations managed by blockchain, using AI and the Unreal Engine, plus tools supplied by Animechain.ai. WaveHack Global Demo Day is another highlight, with the winning hackathon teams set to win prizes totaling $500,000 and the opportunity to present their Web 3.0 projects at future events such as EDCON and WebX. Finally, the 2nd and 5th Floors are exclusive zones that will provide an opportunity for entrepreneurs and innovators to meet and share their vision with some of the most renowned venture capital investors in the crypto industry. Japan Blockchain Week 2024: A Spectacular Series Of Web 3.0 Events Japan Blockchain Week Summit is the new name for the annual Non Fungible Tokyo event that was first held back in 2018, and it is expanding to become one of the top crypto events on the planet, with more than 50,000 attendees due to show up at this year’s revamped edition. The event will run for two days within IVS Crypto 2024 KYOTO, co-hosted by JapanBlockchainWeek and N.Avenue, the operator of CoinDesk JAPAN. As the showcase event at IVS Crypto 2024 KYOTO, Japan Blockchain Week Summit will kick off this year’s Japan Blockchain Week 2024, which is set to run from July 4 to July 31 and will see multiple experiences popping up at locations all over the country. Some of the most eagerly anticipated events include "Web3 Future 2024”, which will take place on July 16, hosted by GInco Inc., and “DCENTRAL Tokyo 2024”, a three-day event that’s set to run from July 17 to July 19. Moreover, De University of Ethereum will host the "EDCON TOKYO 2024" event from July 26 to 30, with IVS Crypto/JBW Summit attendees receiving a ticket that includes a number of special perks. Last year’s IVS Crypto was a spectacular success, with more than 150 side events taking place at Kyoto’s famed Nijo Castle, Yasaka Shrine and Heian Shrine. This year’s edition is sure to be even more exciting, with over 300 events planned to take place across Japan, and the IVS KYOTO Executive Committee is delighted to reveal that it’s now looking for additional event organizers to expand what will surely be one of the most monumental shindigs in the history of Web 3.0. Those interested in participating can visit this link to find out more: https://www.notion.so/headlineasia/IVS2024-SIDE-EVENT-Guide-5903e36440cf474f8e13373d81d4211d . https://www.notion.so/headlineasia/IVS2024-SIDE-EVENT-Guide-5903e36440cf474f8e13373d81d4211d https://www.notion.so/headlineasia/IVS2024-SIDE-EVENT-Guide-5903e36440cf474f8e13373d81d4211d IVS Crypto 2024 is made possible by numerous partnerships and sponsorships with some of the biggest names in Japan’s Web 3.0 industry. Platinum partners Aptos and Animechain.ai, will be joined by a host of Gold partners, including Oasys, double jump.tokyo, Avalanche, Alibaba Cloud,  Japan Open Chain, SBI Holdings, LINE NEXT/DOSI/kaia, and Vyvo Smart Chain, as they work together to build the next generation of the (decentralized) internet. Companies and organizations interested in sponsoring can check details and make inquiries through a dedicated form on the official website. For other partners, please use our dedicated partner application form. Sponsorship inquiry form: https://www.ivs.events/about-sponsorship . https://www.ivs.events/about-sponsorship https://www.ivs.events/about-sponsorship Media partner, community partner, and VC partner guidebook: https://www.notion.so/headlineasia/English-Guidance-for-Partners-of-IVS2024-26c7790de96045ba9645f68672601561 . https://www.notion.so/headlineasia/English-Guidance-for-Partners-of-IVS2024-26c7790de96045ba9645f68672601561 https://www.notion.so/headlineasia/English-Guidance-for-Partners-of-IVS2024-26c7790de96045ba9645f68672601561 For discounted tickets visit: https://www.ivs.events/crypto . https://www.ivs.events/crypto https://www.ivs.events/crypto Coupon code: MarketAcross About the IVS KYOTO Executive Committee Headline Japan, Inc. was established with Kyoto Prefecture and Kyoto City for the purpose of  further developing the startup ecosystem and promoting the local industry through IVS in Kyoto.  We will promote the fusion of startups with Kyoto's corporate, university, research, and cultural  resources, leading to the creation of new industries and the emergence of startups that can  compete on a global scale. Contact Fukaya, Kurita, Togawa & Yoshida ivs-pr@vectorinc.co.jp +81 3-5572-6063 This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Announcing IVS Crypto 2024 KYOTO And Japan Blockchain Week Summit

IVS Crypto 2024 KYOTO এবং জাপান ব্লকচেইন উইক সামিট ঘোষণা করা হচ্ছে

Ankündigung von IVS Crypto 2024 KYOTO und Japan Blockchain Week Summit

Anuncio de IVS Crypto 2024 KYOTO y la Cumbre de la Semana Blockchain de Japón

Annonce du sommet IVS Crypto 2024 KYOTO et Japan Blockchain Week

IVS क्रिप्टो 2024 क्योटो और जापान ब्लॉकचेन सप्ताह शिखर सम्मेलन की घोषणा

IVS Crypto 2024 KYOTOとJapan Blockchain Week Summitのお知らせ

IVS Crypto 2024 KYOTO 및 Japan Blockchain Week Summit 발표

Anunciando IVS Crypto 2024 KYOTO e Japan Blockchain Week Summit

Анонсируем саммит IVS Crypto 2024 KYOTO и Japan Blockchain Week

IVS Crypto 2024 KYOTO ve Japonya Blockchain Haftası Zirvesi Duyurusu

Công bố Hội nghị thượng đỉnh Tuần lễ Blockchain của KYOTO và Nhật Bản IVS Crypto 2024

宣布 IVS Crypto 2024 KYOTO 和日本区块链周峰会

The cryptocurrency world is a rapidly evolving landscape, with new projects, technologies, and investment opportunities emerging what feels like every single day. In this fast-paced environment, having access to comprehensive and up-to-date data is crucial for everyone from developers to traders to analysts. That's where crypto data APIs come into play. These powerful tools provide programmatic access to aggregated market data, on-chain metrics, price feeds, asset metadata, and more from thousands of blockchain networks and crypto exchanges. By tapping into these APIs, builders can create cutting-edge apps that put a wealth of cryptocurrency intelligence at users' fingertips. Apps You Can Build When You Have Access to Robust Crypto Data Streams Trading Platforms and Tools For traders, having access to historical price data alongside live market tickers is like giving a fighter pilot their instrument panel. By integrating a crypto data API like CoinGecko, developers can build advanced trading terminals that display candlestick charts, depth charts, order books and more for thousands of trading pairs across centralized and decentralized exchanges. But it goes beyond just visualizing the data. With flexible API access, you can calculate complex technical indicators on the fly, backtest automated trading strategies against years of historical data, and execute trades directly through the API. Essentially, you have all the building blocks to create a comprehensive trading platform or analysis toolkit. Perhaps most powerfully, machine learning can be layered on top to create self-teaching algorithms that identify patterns in the market data and execute trades based on those patterns. The possibilities are endless when you combine crypto data with AI/ML capabilities. Portfolio Tracking and Crypto Finance Apps For anyone holding a diversified basket of crypto assets, whether they're a day trader or long-term investor, keeping track of your portfolio across dozens of wallets and exchanges is a headache. But it doesn't have to be. By integrating coin metadata like ticker symbols, logos, descriptions and links to blockchain explorers from crypto data APIs, developers can build intuitive portfolio tracking apps that automatically sync all of a user's asset balances and provide a clean interface to monitor performance over time. The metadata also enables more advanced functionality like pricing in fiat terms, profit/loss calculations, and tax reporting features. We're just scratching the surface of ways to improve crypto finance management UX thanks to centralized access to this data. Analytics for DeFi, NFTs, DAOs and Web3 The decentralized finance (DeFi) space is booming, with on-chain trading volumes and total value locked hitting new highs seemingly every month. Projects in the NFT, DAO, and broader Web3 sectors are also seeing an explosion of activity and engagement. But analyzing the trends and opportunities in these areas requires robust on-chain data - information about liquidity pools, orders, trades, mints, token distributions, and more flowing directly from the blockchains where this activity is happening. This is exactly the type of data that crypto APIs like CoinGecko are focused on aggregating and expo sing through clean APIs. Whether it's a dashboard monitoring major DeFi lending activity, an analytical tool that identifies the hottest new NFT collections, or a data viz that maps the connections between the thousands of DAOs, on-chain crypto data is the key ingredient enabling the next wave of blockchain analytics and intelligence apps. Dig into the capabilities of a platform like CoinGecko and you'll find API endpoints that let you track stats on over 500 different decentralized exchanges, pull granular order book data for DEX trading pairs, analyze token transfers and smart contract interactions, and much more. In a space that is inherently decentralized with no single source of truth, having an aggregator that seamlessly combines on-chain data across networks into unified APIs is a game-changer for those of us building Web3 apps, services, and tooling. The Future: How Crypto Data + AI Will Transform Industries As transformative as crypto data APIs have already been for the development of blockchain and cryptocurrency applications, we're really just seeing the tip of the iceberg in terms of their potential impact. I'm most excited about the future intersection of crypto data and artificial intelligence. Being able to combine the wealth of data accessible through API streams with large language models, computer vision, simulation environments, and other cutting-edge AI technologies is going to open up entirely new frontiers of innovation. We're already starting to see examples of this convergence in the form of crypto trading bots that use machine learning to identify patterns and automatically execute trades. But I expect we'll see AI-powered crypto apps and services start to proliferate across domains like: Financial services: Intelligent crypto robo-advisors that provide personalized portfolio management, lending, trading and financial planning guidance tailored to each individual's risk profile and situation


Regulatory compliance: AI models that analyze on-chain activity and transaction patterns to detect fraud, money laundering and other illicit activity in real-time.


Economic simulation: Virtual environments for simulating and testing new blockchain-based economic, financial and governance models before deploying them in the real world.


Asset discovery: AI assistants that can analyze millions of data points to identify up-and-coming crypto assets, DeFi protocols and NFT collections before they explode in popularity.


Gaming and virtual worlds: Open-world blockchain games and metaverse experiences that leverage AI for creating infinite environments, stories, characters and experiences that respond intelligently to players' actions. The possibilities are truly mind-boggling when you have a torrent of live crypto data streaming in that can be consumed and learned from by artificial intelligence models with each passing second. At this pivotal moment when blockchain data is proliferating rapidly but is largely siloed across different networks and platforms, crypto data aggregators and their standardized APIs will act as critical connective layers. They'll provide the canonical pipelines for getting all of that on-chain information into the machines that will shape our decentralized digital future. This grand vision may still be a few years away, but the foundations are being built today by platforms working to comprehensively organize and expose the full scope of crypto asset data. For developers who want to start putting these powerful building blocks to use, there's never been a better time to start plugging into crypto's open data streams through robust APIs. Integrate once, and you'll be able to build apps and services that can interface with the entire blockchain ecosystem as it continues its exponential expansion. Just like the internet opened up entirely new worlds of innovation by democratizing information flows, crypto data APIs are the on-ramp to uncovering value in the vast frontier of decentralized data and assets. Put on your builder helmet and start plugging in. The cryptocurrency world is a rapidly evolving landscape, with new projects, technologies, and investment opportunities emerging what feels like every single day. In this fast-paced environment, having access to comprehensive and up-to-date data is crucial for everyone from developers to traders to analysts. That's where crypto data APIs come into play. These powerful tools provide programmatic access to aggregated market data, on-chain metrics, price feeds, asset metadata, and more from thousands of blockchain networks and crypto exchanges. By tapping into these APIs, builders can create cutting-edge apps that put a wealth of cryptocurrency intelligence at users' fingertips. Apps You Can Build When You Have Access to Robust Crypto Data Streams Trading Platforms and Tools For traders, having access to historical price data alongside live market tickers is like giving a fighter pilot their instrument panel. By integrating a crypto data API like CoinGecko, developers can build advanced trading terminals that display candlestick charts, depth charts, order books and more for thousands of trading pairs across centralized and decentralized exchanges. But it goes beyond just visualizing the data. With flexible API access, you can calculate complex technical indicators on the fly, backtest automated trading strategies against years of historical data, and execute trades directly through the API. Essentially, you have all the building blocks to create a comprehensive trading platform or analysis toolkit. Perhaps most powerfully, machine learning can be layered on top to create self-teaching algorithms that identify patterns in the market data and execute trades based on those patterns. The possibilities are endless when you combine crypto data with AI/ML capabilities. Portfolio Tracking and Crypto Finance Apps For anyone holding a diversified basket of crypto assets, whether they're a day trader or long-term investor, keeping track of your portfolio across dozens of wallets and exchanges is a headache. But it doesn't have to be. By integrating coin metadata like ticker symbols, logos, descriptions and links to blockchain explorers from crypto data APIs, developers can build intuitive portfolio tracking apps that automatically sync all of a user's asset balances and provide a clean interface to monitor performance over time. The metadata also enables more advanced functionality like pricing in fiat terms, profit/loss calculations, and tax reporting features. We're just scratching the surface of ways to improve crypto finance management UX thanks to centralized access to this data. Analytics for DeFi, NFTs, DAOs and Web3 The decentralized finance (DeFi) space is booming, with on-chain trading volumes and total value locked hitting new highs seemingly every month. Projects in the NFT, DAO, and broader Web3 sectors are also seeing an explosion of activity and engagement. But analyzing the trends and opportunities in these areas requires robust on-chain data - information about liquidity pools, orders, trades, mints, token distributions, and more flowing directly from the blockchains where this activity is happening. This is exactly the type of data that crypto APIs like CoinGecko are focused on aggregating and expo sing through clean APIs. Whether it's a dashboard monitoring major DeFi lending activity, an analytical tool that identifies the hottest new NFT collections, or a data viz that maps the connections between the thousands of DAOs, on-chain crypto data is the key ingredient enabling the next wave of blockchain analytics and intelligence apps. Dig into the capabilities of a platform like CoinGecko and you'll find API endpoints that let you track stats on over 500 different decentralized exchanges, pull granular order book data for DEX trading pairs, analyze token transfers and smart contract interactions, and much more. In a space that is inherently decentralized with no single source of truth, having an aggregator that seamlessly combines on-chain data across networks into unified APIs is a game-changer for those of us building Web3 apps, services, and tooling. The Future: How Crypto Data + AI Will Transform Industries As transformative as crypto data APIs have already been for the development of blockchain and cryptocurrency applications, we're really just seeing the tip of the iceberg in terms of their potential impact. I'm most excited about the future intersection of crypto data and artificial intelligence. Being able to combine the wealth of data accessible through API streams with large language models, computer vision, simulation environments, and other cutting-edge AI technologies is going to open up entirely new frontiers of innovation. We're already starting to see examples of this convergence in the form of crypto trading bots that use machine learning to identify patterns and automatically execute trades. But I expect we'll see AI-powered crypto apps and services start to proliferate across domains like: But I expect we'll see AI-powered crypto apps and services start to proliferate across domains like: Financial services: Intelligent crypto robo-advisors that provide personalized portfolio management, lending, trading and financial planning guidance tailored to each individual's risk profile and situation Regulatory compliance: AI models that analyze on-chain activity and transaction patterns to detect fraud, money laundering and other illicit activity in real-time. Economic simulation: Virtual environments for simulating and testing new blockchain-based economic, financial and governance models before deploying them in the real world. Asset discovery: AI assistants that can analyze millions of data points to identify up-and-coming crypto assets, DeFi protocols and NFT collections before they explode in popularity. Gaming and virtual worlds: Open-world blockchain games and metaverse experiences that leverage AI for creating infinite environments, stories, characters and experiences that respond intelligently to players' actions. Financial services: Intelligent crypto robo-advisors that provide personalized portfolio management, lending, trading and financial planning guidance tailored to each individual's risk profile and situation Financial services: Intelligent crypto robo-advisors that provide personalized portfolio management, lending, trading and financial planning guidance tailored to each individual's risk profile and situation Financial services: Regulatory compliance: AI models that analyze on-chain activity and transaction patterns to detect fraud, money laundering and other illicit activity in real-time. Regulatory compliance: AI models that analyze on-chain activity and transaction patterns to detect fraud, money laundering and other illicit activity in real-time. Regulatory compliance: Economic simulation: Virtual environments for simulating and testing new blockchain-based economic, financial and governance models before deploying them in the real world. Economic simulation: Virtual environments for simulating and testing new blockchain-based economic, financial and governance models before deploying them in the real world. Economic simulation: Asset discovery: AI assistants that can analyze millions of data points to identify up-and-coming crypto assets, DeFi protocols and NFT collections before they explode in popularity. Asset discovery: AI assistants that can analyze millions of data points to identify up-and-coming crypto assets, DeFi protocols and NFT collections before they explode in popularity. Asset discovery: Gaming and virtual worlds: Open-world blockchain games and metaverse experiences that leverage AI for creating infinite environments, stories, characters and experiences that respond intelligently to players' actions. Gaming and virtual worlds: Open-world blockchain games and metaverse experiences that leverage AI for creating infinite environments, stories, characters and experiences that respond intelligently to players' actions. Gaming and virtual worlds: The possibilities are truly mind-boggling when you have a torrent of live crypto data streaming in that can be consumed and learned from by artificial intelligence models with each passing second. At this pivotal moment when blockchain data is proliferating rapidly but is largely siloed across different networks and platforms, crypto data aggregators and their standardized APIs will act as critical connective layers. They'll provide the canonical pipelines for getting all of that on-chain information into the machines that will shape our decentralized digital future. This grand vision may still be a few years away, but the foundations are being built today by platforms working to comprehensively organize and expose the full scope of crypto asset data. For developers who want to start putting these powerful building blocks to use, there's never been a better time to start plugging into crypto's open data streams through robust APIs. Integrate once, and you'll be able to build apps and services that can interface with the entire blockchain ecosystem as it continues its exponential expansion. Just like the internet opened up entirely new worlds of innovation by democratizing information flows, crypto data APIs are the on-ramp to uncovering value in the vast frontier of decentralized data and assets. Put on your builder helmet and start plugging in.

How Crypto Data APIs and AI are Shaping the Future of Finance and Technology

AI Is Changing How Developers Learn: Here’s What That Means

এআই পরিবর্তন করছে কীভাবে বিকাশকারীরা শিখতে পারে: এখানে এর অর্থ কী

KI verändert die Lernweise von Entwicklern: Das bedeutet das

La IA está cambiando la forma en que aprenden los desarrolladores: esto es lo que eso significa

L’IA change la façon dont les développeurs apprennent : voici ce que cela signifie

AI डेवलपर्स के सीखने के तरीके को बदल रहा है: जानिए इसका क्या मतलब है

AI が開発者の学習方法を変える: それが何を意味するのか

AI는 개발자의 학습 방식을 변화시키고 있습니다. 이것이 의미하는 바는 다음과 같습니다.

A IA está mudando a forma como os desenvolvedores aprendem: eis o que isso significa

ИИ меняет способ обучения разработчиков: вот что это значит

Yapay Zeka, Geliştiricilerin Öğrenme Şeklini Değiştiriyor: İşte Bu Ne Anlama Geliyor?

AI đang thay đổi cách các nhà phát triển học hỏi: Đây là ý nghĩa của điều đó

人工智能正在改变开发人员的学习方式：这意味着什么

100 Complex Cryptocurrency Terminologies Explained in a Single Sentence

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