FAST AI Movies

There are tons of audio recording apps in the app store, but you know things will be a bit different if Google developed a brand new one. Google recently released a new ‘ ’ app that is powered by its state-of-the-art Machine Learning algorithm that can transcribe what it hears with impressive precision in real-time. This is not the first time Google tried to bless its product with some AI ‘superpower’. Some of their prior attempts failed (I’m talking to you !) and some had quite formidable success, for example, Google’s Pixel phone camera app. Recorder Google Clips With the camera hardware spec a little below industry mainstream, Google’s Pixel flagship phone managed to pull off as thanks to its Machine Learning algorithms for image post-processing. The ‘Recorder’ app is yet another attempt by Google to spice up competition using AI, this time on audio. one of the best smartphone cameras on the market After digging deeper into what the app can do differently and how AI played a core role in it, I found some very interesting insights on how Google handles app, AI and user experience that could shed some light on future app development in the AI-era. What is Google Recorder? You can refer to the following short YouTube video on what Recorder does. In short, you can use it to do real-time transcription, search recorded audio by keywords, automatically generate tags or segment the audio into different categories like music, speech, etc. I’ve been using it for more than a week and found it to be useful, slick and pleasant to use. Recording audio is not a complicated task, but the AI part makes it even easier. I can see this little app makes a big difference for students and people attending meetings regularly. #1 Adoption of Edge-First Model Design (Source: WishDesk ) We all heard of the term ‘Mobile-First Design’. When companies develop their applications, they will design and optimize their app based on mobile experience first, then to other platforms like desktop or web. I think the same idea can also be applied to AI-powered application design, hence ‘Edge-First Design’. Usually, Machine Learning based applications run on the cloud, this is due to the heavy computation requirements for most state-of-the-art ML models. For enterprise applications, this approach is fine since the hardware is hardly a real issue. But if a company wants to build impactful AI-based apps for the consumers, then a cloud-based system often won’t cut it. Running AI-based apps from the cloud is not only slow but also has serious privacy concerns. Also to the normal consumer, they are used to the snappiness modern mobile apps offers. They can care less whether your app is based on some SOTA models or not, if the experience cannot match the high standard they get used to, boosted by many years of modern smartphone hardware/software development. So putting the AI on the ‘Edge’, e.g. user’s phone, tablet, smart home devices will be a better way to success. (Source: Lann) Google Recorder app did a great job on this. It uses a new model called ‘ ’ that is compact enough to reside on the phone while powerful enough to do real-time transcription. Instead of the traditional ‘pipeline’ approach, the RNN-T model uses a which is growingly more popular to solve complicated problems. Until recently, we’ve seen a lot of research progress being made on increasing the prediction performance by using bigger and bigger models, yet the opposite direction is equally important: Using as compact a model as possible to achieve similar performance so the model can be put on the edge. I expect more research to be done in this area when machine learning matures in the coming years. RNN transducer(RNN-T) single neural network, end-to-end approach #2 Use Different Technology Stack for Performance Another interesting development is the introduction of . Created by the creator of Swift programming language, . It uses open-source Swift language with TensorFlow and promises both fast development time like Python and high-level performance like C++. has a great on it. With ML moving more and more from research labs to commercial applications, the performance of ML models will play a much bigger role and Swift for TensorFlow has great potential on that. According to the founder of , Jeremy Howard: Swift for TensorFlow Chris Lattner Fast.ai introductory course fast.ai What's New in Machine Learning - WWDC 2019 - Videos - Apple Developer “Swift can match the performance of hand-tuned assembly code from numerical library vendors. Swift for TensorFlow is the first serious effort I’ve seen to incorporate differentiable programming deep into the heart of a widely used language that is designed from the ground up for performance” #3 Privacy Matters (Source: Matthew Henry on Unsplash ) One of the biggest concerns for AI applications is privacy. For AI to really show value, it has to know a lot about the user, often times their personal life details people don’t feel comfortable sharing. Take audio recording as an example, you might want to record your family meeting discussing your next Christmas plan but don’t want it to be transferred onto the cloud and get 10 Christmas travel agents calling you to sell their products. This gives ‘offline’ ML apps an advantage. Since the model is deployed locally on the edge and no data need to be transferred to the cloud, the user can feel assured that their privacy can be protected. The Recorder app runs all the models on-device and makes it a bit less reluctance for people to adopt it. #4 User Experience Design is Still the Key The Recorder app has a very slick and elegant UI. It’s a simple app with minimal clutters. You can easily start/pause your recording, toggle between ‘Audio’ or ‘Transcript’ mode to check your recorded content and getting suggestions on tags from the content recorded. All works without friction. During recording, the app will automatically categorize sections of audio as ‘Speech’, ‘Music’, ‘Whistling’ … etc. and color code them accordingly. When playback your recorded audio, you can see each word get highlighted when being spoken in the transcript mode and you can search through the transcripts use the keyword you want. Very intuitive. What I’m trying to say is: User experience design will make or break a great AI model. Only when working seamlessly with other parts of the app can an AI feature delivers its value to the end-user. A model that can address the user’s paint-point with high performance is only a start, not the end. AI should serve silently behind the scenes rather take the center stage. #5 Responsiveness Come with a Price In the mobile world, companies strive to offer more responsiveness. Consumers nowadays are very impatient and the last thing they want is to wait. Snappy experience means the user can focus on the content they want or the tasks at hand. But responsiveness on mobile devices is not easy to come by. Computing power, screen size, system resources are all very limited compare to desktop or cloud. To achieve the best responsiveness, more thoughts and research need to be put into the design and development of the app. This includes better use of CPU/GPU, memory optimization, choose fast programming languages for the implementation and reduce dependence on back-end servers. The Machine Learning industry has made great progress on research for the past few years, yet to have more impact on people’s day-to-day life, more investment and work has to be done on the engineering side. And a switch from research to engineering is a sign of matureness for new technology. The Right Way of Developing AI Applications? Image from Overwatch (Source: Overwatch) People have this fantasy of scary AI taking over humanity for many years. Movies, novels, TV Shows all painted a very dramatic future of AI for mankind. To counter this public (biased?) impression on AI, special cautions need to be taken. It’s beneficial to adopt an ‘AI exist as a tool to help human’ mentality instead of an ‘AI vs Mankind’ one. AI can do a lot of things, but rather than develop AI apps that can ‘replace’ humans, it’s better to have AI that exists to help humans perform their tasks easier and faster. Like the Recorder app to help taking notes, image recognition systems to help the doctor diagnose better, augment reality app to help people better navigate the neighborhood, etc. A quiet, friendly, yet powerful AI diligently working behind the scenes to help people do whatever they do better is so much more comfortable and approachable for people, compare to a robotic killing machine in a SciFi movie. Previously published at https://towardsdatascience.com/5-things-i-learned-from-googles-new-ml-powered-recorder-app-6c9616a05b78

5 Things I Learned from Google’s New ML-Powered Recorder App

It was a dark, grey winters evening and I found myself, as I had done way too many times in the past, staring at my computer screen endlessly scrolling through useless articles ranging from snowflaky self-help to brain melting tutorials. Phew, that was a long sentence. Anyways, for reasons I can’t remember I found myself reading this article: https://www.digitaltrends.com/cool-tech/japanese-ai-writes-novel-passes-first-round-nationanl-literary-prize/ An AI wrote a novel, and whats more, it almost won a literary prize! So, not only was it not garbage, it was good enough to fool the experts! I was intrigued, and started googling away… I found out that there actually is a where people submit their best attempt at generating a novel that is at least 50,000 words. I looked at some of the code/outputs and was really intrigued. You can find it here: National Novel Generation Month https://github.com/NaNoGenMo And then as if I wasn’t frothing in the mouth from excitement already, I read this: https://github.com/zackthoutt/got-book-6 A guy wrote the next game of thrones book using deep learning! All sorts of thoughts raced through my head. I could see it now… I was going to take some data and put it through my amazing algorithm. I was going to publish a novel. It was going to become a best seller. The next big fantasy series. I’d be doing pretty well with book sales. Netflix would then come and secure rights to my book. They would make a trilogy of movies. I’d get to meet Jennifer Lawrence. I’d be doing really well now. They would invite me for an interview on TV. The interviewer would gush at my work and tell me how she’s such a big fan and ask me what’s the secret to my, seemingly, superhuman ability to produce so many amazing novels. I’d give her a smug grin, look at the camera, and shout: “Haha, you idiots! I just fed all the Wheel of Time books through an algorithm I stole from github from some random dude! You’re like the people in that Al Pacino movie where he makes that Simone software. You got Simoned!” Pandemonium would break out. People would start questioning their reality. They would be afraid to pick up another book in case their favorite author turns out to be a machine. I couldn’t wait. I set about executing my devious plan. 30 minutes later… I gave up. Yeah, turns out most algorithms are not that great at churning out good novels. In fact, they produce really incoherent, and kind of funny, outputs: “i had inherited the company because of the future putting his brother in applause. parents was a stupid success, madam, now indeed, and female form in individual color. now the rant happened and closet, maiden, always won for any present, in six.” I clearly wasn’t going to be impressing anyone, let alone Netflix and Jennifer Lawrence, with that prose. I was disappointed. I had no experience in deep learning and no resources to consume a ridiculous amount of data, so I could scarcely hope to beat these efforts made by so called experts. If only there was genre where these random words could be interpreted as genius. And then it hit me. Poetry! What is poetry but a bunch of random words thrown together? It’s the equivalent of modern art in literature. Okay, I apologize to anyone who loves and reads poetry. I am sure it can be beautiful and meaningful. But it’s never really appealed to my unsophisticated tastes. I tend to prefer a plain worded fairy tale with swords. And dragons. And wise old men with long white beards. But I was curious to try it out and see what kind of output I could get with poetry. So began my little project. Data The Data I decided to use was Walt Whitman’s Leaves of Grass. Even a plebeian like me can appreciate Walt Whitman! You can find this at Project Gutenberg which is a resource for non-copyright works or those that are now in the public domain: https://www.gutenberg.org/ I found the text file for Leaves of Grass and saved it down on my computer. Let’s call it data.txt. Algorithm I decided to use Zach Thoutt’s algorithm which he had used to generate the next book of Game of Thrones: https://github.com/zackthoutt/got-book-6 Where do I run this? One thing you need to know about deep learning is that you need of computing power to run the models. Ideally, you need a GPU resource to do the heavy lifting for you. I did not have a GPU in my possession but luckily I had dabbled (emphasis on the dabble) with deep learning before and signed up for Jeremy Howard’s course on it: a lot http://www.fast.ai/ In the fast.ai course you run all your models on the cloud so you are not constrained by your machine. We setup an EC2 instance on Amazon Web Services (AWS) which has the GPU power behind it (this would be the P2 instance). You need to request Amazon to give you access to this; which you can if you are a member of his course. Once you have your instance running, you then run your code in a Jupyter notebook hooked up to that instance. I felt that setting up all this to run your deep learning model was a pain for a layman like me so I am going to do a step-by-step walkthrough on how to do this. Now, there are many ways to do this. But I am just going to show you the way I did it. It might not be the best way. But it works. Finally, the tutorial I am assuming you know how to start EC2 instances. For this, you want to use one of the AWS Deep Learning AMI. This way you do not have to worry about installing any of the deep learning packages. I selected the AWS Deep Learning AMI (Amazon Linux). Now, select a p2 instance. This would probably be the p2.xlarge instance unless you’re a big shot who got approved for an even bigger instance. Once you are okay with everything, launch your instance. Now, open up a terminal and connect to your EC2. You know the drill: use the terminal in Mac or Putty in windows. You can find out how to SSH into your instance by right clicking on your EC2 instance and choosing the Connect option. The command will be similar to this: ssh -i your-ec2-key.pem ec2-user@ec22–212–21–23–21.compute-1.amazonaws.com You’re in! And everything is already setup because we selected the Deep Leaning AMI. Well, everything except for a few tiny things… One of the libraries used for deep learning is Tensorflow. We want to use Tensorflow version 1.0.0 for this exercise. The reason is that the github code we will be using breaks on later versions. It’s probably a simple enough update to change the code to fix this but I am lazy and just want to run this ****. We need to change our version by first uninstalling the existing Tensorflow package and re-installing 1.0.0. #Uninstallpip uninstall tensorflow # Install version 1.0.0pip install tensorflow==1.0.0 Then we need to optimize our GPU settings because Amazon for some reason does not do this automatically: # optimize GPUsudo nvidia-persistencedsudo nvidia-smi — auto-boost-default=0sudo nvidia-smi -ac 2505,875 Another thing we need to do to insure that our deep learning algorithm actually uses the GPU on this instance is to set the library path for CUDA: export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64 Done! Now we are ready to start up Jupyter. You need to run this command: jupyter notebook --no-browser --port=8888 Obviously, this is not straightforward as well. You need to now open up a new tab/window in your terminal. And run this command (with your key and EC2 ID) so you can run Jupyter on local host 8000: ssh -i EC2key.pem -L 8000:localhost:8888 ec2-user@ec2-21-21-21-21.compute-1.amazonaws.com Okay! Now we are really ready to start coding aka copy pasting someone else's code. Open up localhost:8000 and you should see Jupyter starting up. You might need to authenticate to access it in which case you need to pass in a string in the URL. This can be found in the output in your terminal where you ran the Jupyter notebook command. Now, we need to move the data inside our notebook. I am assuming you’ve been a great follower and have already saved down the data. We called it . You can easily move this into Jupyter by using the Upload button at the top right of your home page. data.txt On your right there is a button titled Upload. Now our data is in Jupyter, all we have to do is to use our stolen code on it! You can grab the notebook which has the code here: https://github.com/zackthoutt/got-book-6/blob/master/got-book-generator.ipynb Either copy paste it or move the whole notebook via the upload command into your Jupyter server. Change the reference in the code to your data book_filenames = sorted(glob.glob("/data/*.txt")) Becomes: book_filenames = sorted(glob.glob("data.txt")) And now you just hit run and go through each of the Cells from top to bottom! Once you train your model (and you can play around with the hyperparameters), you can pick a word and generate a sample of Whitmanesque poetry. It should be saved under an outputs folder on your Jupyter homepage. Here is a sample: i hear the new river-stripes of the western sky,the engulfed wanderings with them throughwhat thou side to the rest, lilacs out at the music, shouting, long, unbereav’d, henceforth in thy task music,here with seed mere purpose more without drop or century enough o people, farther with india!centuries a bunting! always me pleas’d and her time or land!corroborating for the sands of talk and pause toward him,the war wreck’d, the best of hand, then freely alone,endless along the seas,endowoutside aside and his faceof america’s forehead,manhattan in the north as all the golden ground,down through many a distant armies, standing for your brother? Look at that. It makes no sense. But maybe it does? It’s genius is what I say. Now you too can become the next James Joyce and they’ll be trying to figure out what you meant for years to come. Here’s another one: rocks and foam of victory, time and crossing night,however rock the voice andgeneral quickly lovers,we stand no more playing out plan from your aims, libertad,all walk,in the ruins of the two the heroes slowlybusy with her — the odds of the rest prepared,, to its know puts herearound — touch,my comrade at mechanics withwoe,after i at lanes and space beautiful out so well — done now the sun with all their turn there are in last,bright out of the interminable convulsive, journeying, thistheir spheres,for my hands back over the white hand in a swamp,i know as feudal voice, inseparably coarse and round hand is so,till i hear the carol wash’d cubic instruments, and bear close its hoarse steps in the frozen sentry,the builder, corner’d and desperate, an creatures,the shy and odour to, the sailors the arrogant small, and ringing the splashing rolls whirl sat,out and the real cover years overhead rising or tumbling city. Doesn’t it bring a tear to your eye? Also, if your model is taking a long time to run please make sure you are running it on your GPU. You can check this by running: nvidia-smi If it shows a message of No Running Process, even though your model is being trained, it means the GPU has not been hooked up properly. Again, make sure you ran this line: export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64 Hope this was helpful! Please do share your results. I’d be curious to see what you got. :) Bilal

How To Write Poetry Using Deep Learning

This is a redacted version of the by CEO David Smooke and COO Linh Smooke sent to 1.3k shareholders. Picture: HackerNoon Team in an All-Hands Meeting. HackerNoon shareholders' newsletter TL;DR Revenue is slightly down, traffic is slightly up, rate of product development is up, expenses are down, and AI is assisting us but is not replacing us anytime soon 🙂 How can you help? Referral, referral, referral: we recently experimented with a Business Blogging Sales Referral Program for a 12 or 52-credit pack. If you think you can help refer customers to publish their announcements, blog posts, or technical documentation with HackerNoon, we are more than happy to share the details of the Referral Program with you! Here are some high-level updates since our last shareholder letter, which was . We keep this update succinct, with lots of links sprinkled throughout, as we’ve actually written a throughout the year. sent on June 19, 2023 lot of mini-updates Read the full Blog Post below for full context. 📈 Traffic & Editorial in the Age of AI 📈 HackerNoon Readership & Traffic HackerNoon readership and traffic remain stronger than ever: 2023 (especially the latter half) was a great year for traffic. With for different types of and , simpler micro-engagement mechanisms for users ( , , ), we published 18,659 stories (compared to 13k in 2022), and on-boarded 29k new writers (compared to 22k in 2022). I think this is a huge testament to our human-first (we are documenting our protocol at , which is powered by the HackerNoon CMS). In a world where content is inundated by AI, HackerNoon remains one of the few places on the internet with , , and . simpler sign-up flows users actions open commenting for all published writers polls voting & commenting history for readers easy-peezy templates for aspiring writers editorial protocol EditingProtocol.com a Second Human Rule an AI & Plagiarism Detector 2-way communications between editors & writers Even more encouragingly, we continue to ride this tailwind into 2024 as well: Here’s a list of the top-performing HackerNoon stories/pages in 2023: Niche: by Programming 14 Patterns to Ace Any Coding Interview Question Fahim ul Haq Niche: , by , translated to 7 different languages, including Spanish Cybersecurity Cómo hackear cuentas de Facebook: 5 vulnerabilidades comunes original English version Jessica Truong Niche: by Media The Tom Holland Spider-Man Movies in Order of Release Date Jose Hernandez Niche: by Futurism Apple CarPlay Not Working [SOLVED] How to Fix Common Issues Khunshan Ahmad Niche: , published by Web3 How to Implement a Merkle Tree in Solidity Daniel Shvetsov ! HackerNoon Search And here’s a list of top performing HackerNoon stories/pages YTD in 2024: Niche: 任天堂、パルワールドで沈黙を破る, by , translated into 12 languages, including Japanese Gaming original English version Player Auctions Niche: by Programming How to Read Text File in Python? Srinivas Ramakrishna Niche: , published by Machine Learning Open-Source: The Next Step in AI Revolution MinIO Niche: , published by Product Management To Focus or Not Focus: How to Find the Right Product-Market Fit Denis Pushkin Niche: , published by Tech Companies Apple Customers Return Vision Pro By The Droves Allan Grain page! Why Publish on HackerNoon We’ve continued to scale up audiences via niche newsletter growth. Notably, which is an editor-written weekly commentary on our , has now passed 100 editions and 45k+ subscribers. Additionally, the 22 niche technology newsletters (one for each new category) have been growing steadily and now total 280k+ subscribers. In total, we send well over half a million emails a day (!) The Tech Company Brief, proprietary tech company ranking data AHREFs, the top SEO software, . This is a testament to building up our internet presence over the years, publishing more quality stories day after day and year after year, and the rest of the internet’s willingness to cite and talk about HackerNoon stories. For reference, here are some similarly ranked domains that historically carry much higher valuations, many of which are also community-driven technology education destinations: , , , , , , , , , , , and . Here’s a screenshot from 2/29/24: ranks HackerNoon.com as the 2,750th most valuable domain worldwide Kaggle at 2,802 Heroku at 2,824 Google Earth at 2,861 Delaware at 2,870 NextJS at 2,880 GQ at 2,881 Brown at 2,834 Seeking Alpha at 2,844 Hotels at 2,907 Snap at 2,993 Cal Tech at 2,999 1Password at 3,011 Since we started HackerNoon, we’ve outlived many tech sites and products that we’ve (mostly) admired: , , , , , , , , , , , , , , , , , , , , , , , , , , and of course, . We don’t take joy in these (mostly) impactful businesses dying, but it is a reminder that HackerNoon keeps on blogging. Vice Artifact Protocol Future Apple EV InVision The Messenger, IRL (lol) Meta Portal Buzzfeed News Anki Google+ Microsoft’s Mixer Recur, HouseParty Essential The Outline Bodega Loon LG Phones Nuzzel Mandolin Fast Argo AI, Kite Kitty Hawk Udayy Blackberry (again), Telltale Games Revue Quibi 💰 Revenue & Business Development Net Income 📉amist & in tech & media bear markets mass layoffs Both revenue and expenses are down in 2023 YoY. We made in revenue in 2023, and spent about - a slight dip compared to 2022. Our net income remains level; however, we have some catching up to do in 2024. Our 2024 revenue projection is , and expenses project to be in 2024. We are determined to be profitable again in 2024, 2025, and beyond. redacted redacted redacted redacted Business Blogging We’ve fine-tuned our to include better returns for customers and better margins for HackerNoon. We built a , raised the prices per post and improved the performance per premium post by adding , , , and better customer service. In 2023, we onboarded 609 new businesses and published 1,624 , averaging a net income of /story (compared to 2022 net income of /story). Business Blogging self-service flow to request a business blogging trial 12 language translations multi-voice audio file creation managed paid social promotion good company stories redacted redacted Encouragingly, so far in 2024, we’ve made about half of our revenue in , surpassing both and . Not only is this good because content is at the heart of our business value prop, but also because this is a true unlimited inventory, independent of past or future traffic, we can always publish another blog post. Business Blogging Niche Ads Writing Contests Additionally, we’ve seen an increased demand to publish press releases from wire services, with customers such as , , , and . We’re building a custom technology press release solution that includes distribution across traditional press release sites in addition to business blogging’s default, social, audio, multi-lingual, email, and on-site distribution. ChainWire FinanceWire GamingWire BTCWire Business Database Scale Up with and Startups of the Year Evergreen Tech Company News Pages Startups of the Year 2023 concluded with ! The winners and nominees were excited, you can see a taste of their enthusiasm on , , and . Our evergreen news pages are up to covered (ranking S&P 500, public companies, and startups alike). Companies with a regular to an Evergreen Premium with more control over their internet presence. Our is also hosted on ( & ) and ! over 623k votes, 30k startups, and 1k+ winners Twitter/X J) LinkedIn around the web 12k+ total companies Evergreen Page can claim, edit and also upgrade their page unique dataset curating the news about these companies Hugging Face their CEO CTO commented reused by MongoDB Vertical Category Curation Diversifies Streams of Income We curated our entire library of 100k+ stories and into . This divides the library into 22 starting points, like , / , / , to name a few. Advertisers now buy entire categories to ensure across our site. We made combined in Niche Ads & Billboard ads in 2023, compared to the total in Billboard alone in 2022. That means each pageview on the page is worth 11% more! 50k tags 22 categories /ai cloud business content-relevant ad placements redacted redacted HR, Payroll Reduction, “trimming the fats” Both David & Linh have taken a payroll reduction in 2023 by 50%, and we will continue to cut our salaries significantly in 2024 until the company gets back on track. We’ve also reduced our staff by half. HackerNoon started 2023 with 40 staff members and started 2024 with only 20. Experiments with new inventories in 2023 and beyond We introduced with our European partner, . We learned in 2022 & 2023 that convert more advertisers & long-term business partners than our regular top-nav billboard ads. HackerNoon’s Job Board Jobbio targeted, niched and relevant ads We also launched the ! This is proof of concept for a docu-series on the future of the internet. It costs $2.99 and is a great way to spend 30 minutes of your time while supporting HackerNoon. HackerNoon Documentary In 2024, we are thoughtfully looking into programmatic ads to capitalize on our stable, quality traffic more efficiently. 🚀 Infrastructure Overhaul & Product Development HackerNoon 3.0 The great refactoring. As a platform that makes software completely in-house, we get to choose . Starting mid-2023, we’ve decided to migrate our backend database from Firestore/Google to Mongodb, our frontend tech from Vercel premium to a combination of Vercel/Svelkit, and our email host from Sendgrid to Elastic. Removing Firestore greatly reduces the number of reads we pay for, and removing SendGrid greatly reduces the cost per email sent.  Not only will these refactorings make HackerNoon lighter, simpler, and more efficient, but they will also help reduce our cost of production by an estimated 25-35%. which technology companies to partner with ( , ) HackerNoon Mobile App Apple Google Our mobile app officially and has gone through 9 iterations already since September 2023! We were briefly the in the US, Vietnam, Brazil, and Ukraine during launch month. (version ), users can , , , and any story to HackerNoon. And we added 12 additional languages to read our prime library of technology stories. This update is a commitment to helping technologists to not only more easily create content but also to reach and serve worldwide readers from their mobile devices. launched top 100 apps With the latest version 1.9 read write listen submit More mobile app release notes. Niche Technology Publication Network powered by the HackerNoon CMS (beta) In just a few clicks, a HackerNoon account can turn into a standalone site. This year, we are building a 500+ owned network of sites via the HackerNoon CMS with a focus on curating and distributing the world’s highest-quality open-source content. HackerNoon sites are now going live every week. Some WIP examples include: , , , , , , , , , , , , , , , , , , , , , , , and more coming soon! LearnRepo.com Memeology.tech HackerNoon.tech EditingProtocol.com Escholar.tech TextModels.tech Blog.DavidSmooke.Net HackerNoon.LinhDaoSmooke.com PublicDomain.tech LegalPDF.tech OpenDatasets.tech Roasts.tech CompanyBrief.tech StoryTemplates.tech SupportNoon.com UnknownAuthor.tech Noonion.tech HackerEvents.tech DearElon.tech Blog.Slogging.com CoinWikis.com Noonification.com HistoricalEmails.com Beautiful Landing Pages powered by the HackerNoon CMS We also started to host many pages in-house using our own page-builder as opposed to using 3rd party CMS like Squarespace, Wix, or Strikingly. Examples of some of these in-house landing pages using our own page builder Include: , , ( ,  # , # , # ), , , ( , , ), & . HackerNoon Mobile App Web 2.5 Why Publish Pages Content Startups AI Programming About Page Slogging.com Testimonial Pages Writers Customers Readers Writing Contests Technological Integration In order to make the content management system that powers HackerNoon best in class, we can’t build everything ourselves. Some of the recent notable CMS integrations include: We integrate a lot of best-in-class solutions and technologies. for all published writers. Username.HackerNoon namespaces minted on the blockchain via namespace.gg . AI-written submissions have gone through the roof, but unlike other blogging platforms, we do not blindly publish AI-created content. This cat-and-mouse game will continue to evolve! Originality.ai and other tools for AI Writing Detection (for those visitors currently logged into Google). This one is averaging about 850 new accounts per day 😀 Signup/Signin with Google for easier account creation and login and . This type of content portability increases our rate of publishing. Importing of text transcripts from Youtube Importing of full blog posts from RSS and other blogging platforms to make the site more fun. Added GIPHY to story editing and commenting New search discovery experience and renewed partnership with Algolia Yet another year of our mutually beneficial partnership (we pay them via in-kind ads!) Algolia helps beautifully index and discover our content, while we surface their Ad on & . our search page search bar Steering into the internet’s pixelated ethos and using open source design as an adoption channel are the 1,440 original icons used on HackerNoon, and now they are open sourced and available on , and as This builds on our open source release of the , which is up to Use of our icons and fonts in other sites and apps are subtle endorsements of HackerNoon’s way of publishing, and our network of owned CMS sites will scale up this usage. The Pixel Icon Library GitHub Figma (1.6k users), an NPMjs package. 2.0 version of the HackerNoon font 3k downloads on DaFont. Helping Technologists to Market Themselves HackerNoon and expertise in the technology industry. In addition to (links to your portfolio, newsletter, jobs, or wherever), , and , we now also empower users to and (shipped this week, ). validates contributions entering Call to Actions updating your social media profiles filling out your short and long-form bios flaunt their work and job history rank top writers by technology categories it has writers very excited 💁 How can you help? we recently experimented with a Business Blogging Sales Referral Program for (base value of $4,788 and $15,548 respectively). If you think you can help refer customers to publish their announcements, blog posts, or technical documentation with HackerNoon, we are more than happy to share the details of the Referral Program with you! Referral, referral, referral: a 12 or 52-credit pack Kind Regards, CEO and COO , David Smooke Linh Dao Smooke HackerNoon If seeking more regular updates from HackerNoon, I recommend subscribing to the , , and/or . P.S. #hackernoon-product tag hackernoon.tech the #hackernoon tag Here are some recent news coverage about HackerNoon around the web: P.P.S. , #2 Blogging Platform for Developers by Perplexity AI ( Meeting with Vietnamese Prime Minister Pham Minh Chinh full remarks) , Yale Entrepreneurship Mentor Series , Best AI/ML Blog for Community Engagement by Hosting Advice ( ), AI Time Journal CEO Interview with contextual links ( ), Web3 Founder Interview with contextual links , Financial Interview with Vietcetera , KingsCrowd Empowering Technologists Interview , SuperbCrew Startups Interview , HustleFund Interview about Startup Storytelling , Our Favorite Tweet/Posts on Twitter/X , #14 Crypto Media Source by StealthEx , Stratechery Sharp Tech Podcast Mention , Recommended Tech Blog for Engineers , Unchained Podcast Mention , ROIquant Conference Fireside Chat , #6 AI Blog to Follow by Analytics Insights , #7 Blog for Product Management , Professor Rymel Adding HackerNoon to Her Curriculum , Top Startup Resource by Faster Capital , Top Crypto Blog by Crypto Economy , Must Follow Tech Blog by Xpheno , #3 Programming Blog by Blogging Idol , #6 Layperson-Friendly Resources For Tech News by Forbes : , , . And Testimonials Readers Writers and Businesses

State of the Noonion 2024: HackerNoon Keeps on Blogging

নুনিয়ন 2024 এর অবস্থা: হ্যাকারনুন ব্লগিং চালিয়ে যায়

Stand der Noonion 2024: HackerNoon bloggt weiter

Estado del mediodía 2024: HackerNoon sigue blogueando

State of the Noonion 2024 : HackerNoon continue de bloguer

नूनियन 2024 की स्थिति: हैकरनून ब्लॉगिंग जारी रखता है

2024 年の正午の様子: HackerNoon はブログを書き続ける

2024년 정오 현황: HackerNoon이 계속 블로깅을 하고 있습니다.

State of the Noonion 2024: HackerNoon continua blogando

Состояние полудня 2024 года: HackerNoon продолжает вести блог

Öğlen Durumu 2024: HackerNoon Bloglamaya Devam Ediyor

Trạng thái buổi trưa 2024: HackerNoon tiếp tục viết blog

2024 年 Noonion 状态：HackerNoon 继续写博客

Photo by Andy Kelly on Unsplash Everyone is saying AI is coming for our jobs, and it’s coming fast. Will AI replace humans and create an inevitable worldwide unemployment crisis? Humans are good at surviving and excelling in the real world . . . aren’t they? When hunting and gathering were our only requirements, the development of agriculture didn’t mean the end of life as we knew it. We adapted and evolved. The industrial revolution didn’t result in unemployment armageddon. Instead, humans created more jobs and reinvented themselves with the help of new technologies. The advent of the Internet and the knowledge economy didn’t permanently put us out of work, either. Instead, each of these innovations made us more productive with elimination of very few job categories. Technology and innovation makes our lives easier and helps us do our jobs better. That’s what AI has in store for us. It makes us more efficient — in effect, superhuman. #1. AI frees us from repetitive tasks There are too many repetitive tasks in our jobs. For example, take recruitment. A recruiter’s job is to find talent for organizations. This role involves personal interaction so the recruiter can build relationships with clients and candidates. What they spend way too much time doing is sorting through resumes (often hundreds or thousands), searching through job sites, scheduling interviews, making phone calls, and sending emails. . That frees up the recruiter to take care of what’s really important, like developing relationships with top candidates and getting them into the best jobs. AI can easily handle repetitive recruiting tasks, and it can highlight the best candidates — those with the greatest chance of success in a particular organization That’s win-win situation. #2. AI isn’t smart enough to do creative work AI can plow through a million psychology textbooks in a fraction of a second, then tell you all symptoms of and treatments for depression. But only a human can read a face and instantly know the right thing to say. This is emotional intelligence, which AI simply doesn’t do. And it never will. Our nimbleness to react instantly in very creative ways is unmatched by any computer. The auto suggest feature on your smartphone uses AI to predict the next word you want to type. It helps you type your message faster, but it can’t fully take over and chat with a colleague by feeling, understanding and appropriately reacting to human emotions. Even Google Duplex that has got people scared is designed to operate in very specific use cases such as hair salon booking, restaurant reservations, and holiday hours. AI will only work — and learn — within a given set of constrained parameters, unless is achieved. singularity Google’s AI search algorithm has transformed the research process. You no longer need to crawl through dusty libraries or know the dewey decimal system. Google crawlers and algorithms deliver what you need with uncanny accuracy. You get all the best query results through Google’s ranking system, without any delays for thought or clumsy boolean query strings. AI makes us more effective and more efficient. It gives us back the time we need to do creative work, including reviewing our search results and assimilating the information. #3. AI allows us to be better at our jobs by making us more human Take sales, for instance. Selling is an art that takes incredible finesse to do well. It’s the marketer’s most basic directive and it’s an inherently human function. Salespeople waste time qualifying prospects, sending follow-up emails, and updating client relationship management (CRM) software instead of being dedicated to human interaction and rapport-building. Those with a natural knack for selling might be able to keep up, but the rest of your team isn’t going to be as productive as they should be. When you add AI to the equation, the job gets easier and your sales force gets stronger because now they have time to study and learn from your high performers. AI takes care of unproductive overhead so salespeople can focus on essential tasks like listening and asking questions, empathizing with prospects, and finding creative solutions to problems. When we’re freed from menial work, the world slows down around us. We have more time to strategize, relate with clients, and optimize our processes to increase productivity and get a greater return on investment. #4. AI creates new industries and jobs Who could have predicted that a breed of converted Facebook junkies called social media marketers would create a $31 billion industry leveraging social media? Social media jobs were non-existent 10 years ago. Today, social media managers are earning six figures, on par with the best technology workers. Let me tell you a story from the eighteenth century, when the Spinning Jenny was invented. Workers in the spinning profession were terrified of losing their jobs. The Spinning Jenny reduced the amount of work required to spin thread, which led to a fall in the price of textiles. The cotton spinning workforce was so afraid of losing their jobs that they . Today we have cheap, mass-produced cloth because of the foundation that was laid by the Spinning Jenny — and, contrary to what the workers feared, the affordable thread resulted in uses that expanded the industry even more. broke into the inventor’s house and smashed his machines Considering the improved lifestyle we’ve experienced since this technological disruption, shouldn’t we be similarly excited about AI? Expanding productivity will cause industry to flourish in ways we can’t even imagine. Here’s what’s AI is already doing: AI software is improving elder care as demographic trends overwhelm the care industry. AI-enabled robots are taking over menial and monotonous tasks. It’s leading to more efficient money management, applying the best investment strategies. It’s serving and protecting citizens by enabling effective and unbiased law enforcement. New devices and new technologies will give birth to new industries and jobs, some that are unfathomable today. #5. AI can’t solve healthcare’s major problems You’ve probably seen the Black Panther movie, where Vibranium powered AI solutions are so common that a gunshot to the spine takes only a day to heal. So you might think AI will provide a cure for AIDS next year. Well, that’s just fantasy. There are highly intelligent AI systems like IBM’s that can memorize a bazillion ailments and recommend treatments. But it will be decades before AI finds a cure for cancer or old age, because it lacks the creativity and spontaneity that sparks human genius. Watson We won’t have instant discoveries in healthcare or major world problems just because of AI. Trials, experiments, peer review, and many million lines of code stand in the way. That’s all done by humans. And progress will be slow. But what AI will do is accelerate the process significantly. With artificial intelligence, extremely detailed models and simulations of human cells and other physiological components are possible. These models will boost experiments to the next level and save years of research. We’ll be able to reduce death rates and prolong human life. AI will help us work faster, eliminate impractical solutions, and narrow the pool of promising alternatives. Artificial intelligence: what does the future hold? One of the most interesting things about AI is that, unlike static code, it is programmed to learn. That means it can evolve all by itself. A lot of commentators predict that sometime in the very near , AI will achieve singularity. future At the stage of singularity, AI will become smarter than humans. It might even be able to think, essentially evolving into a new species. If this fiction steps out of sci-fi movies and becomes reality, the human race will face a challenge. Ethicists constantly debate what to do about it. None of that changes the benefits of the explosive AI innovation going on in Silicon Valley and across the globe. IBM’s Watson has tried its hand at several careers, including professional sports scout and medical diagnostician. But, most famously, Watson is a Jeopardy! winner and chess champion. Each of these scenarios was a narrow construction that allowed Watson’s brute force computing power to demonstrate expertise. There’s even AI tech that handles complex problems in financial services. One Hong Kong company . AI bots have also made an appearance in the literary industry, creating interesting work in and . appointed an algorithm as its director poetry prose Not to fear — we can sit back comfortably and look forward to a future where humans and AI work together to solve the world’s problems in real time. Artificial intelligence: legal implications and IP protection AI is a disruptive innovation and isn’t limited to the tech and business sectors. Businesses are getting savvy to the fact that a lot of tricky situations are ahead, especially concerning the legal implications of artificial intelligence. AI pioneers need to protect their intellectual property. Regulation has become a big issue, especially after incidents like the recent fatal accident in Arizona involving an self-driving Uber car. The laws revolve around driver fault, but how do you prove fault when no human is driving the car? Lawmakers are already working to push through legislation to regulate self-driving vehicles, while at the same time trying not to squelch innovation. Issues with IP protection are especially close to home for CEOs and senior executives of companies that design and develop artificial intelligence systems. Today’s tech race is competitive, and intellectual property is its most valuable commodity. The smartphone industry, for example, has shown us that the interval between innovation discovery and its appropriation by competitors can be as short as a few months, in part because so many AI developments are open source. — with AI development getting so much attention. — Businesses need to have a patent strategy to protect their innovations if they want to maintain market dominance or evolve to become a dominant player in their markets Executives can no longer afford to scrape by with minimal knowledge of IP protection while disruptive is continually developed and protected. Focused IP protection strategies need to be unboxed and implemented even before an innovation is market-ready. It’s the only way to stay ahead of the wave AI investment. technology Patents, copyrights and trademarks offer legal protection. But it can be difficult to determine which type provides the best protection for each AI businesses investment. The big question is: How is your company differentiating yourself with your technology? Is your innovation new source code, improved technical functionality, a strong brand, or something completely different? Startups often leverage open-source software (OSS), without the burden of legacy systems, in order to quickly develop AI innovations. OSS licenses differ in their implications on IP protection strategies. Some licenses let you protect your innovation with patents, but restrict you from enforcing them. Most prevent you from excluding other startups or established companies from using the source code you develop on top of the OSS. Even after you’ve decided on a form of protection, seeing it through can present serious challenges. Obtaining a patent in the US typically takes anywhere from 3 to 5 years. While the patent will protect the innovation for up to 20 years, any advantage the company has may be lost while they’re waiting for the patent to go through. Three years is an eternity in Silicon Valley! That’s where fast-tracking your patent can speed the patent office’s decision to a year or less. The process for obtaining a patent can be confusing and can potentially take years to complete. A landmark decision by the US Supreme Court in 2014 puts a big question mark on the possibility that AI solutions can be patented. That’s because the court doesn’t regard ‘abstract ideas’ like ‘disembodied algorithms and formulas’ as patent-eligible. In addition, the very real question of ownership of original works will emerge in the near future when AI helps with innovation. A photographer by animal rights activists who claimed that the copyright in a selfie taken on his camera by a monkey belongs to the monkey, not to him. The future patent tussle won’t be between humans and monkeys, but between humans and AI. was recently sued Current AI practices teach bots to evolve through machine learning. This means they can evolve to the point that they’ll produce output radically different from their source code and, in some cases, even rewrite their own code. When that happens, who will own the copyright, the code writer or the bot? What if the improvement is patentable? The best way to tackle these legal and IP issues is to . An expert can help you develop a robust strategy for protecting your company’s intellectual property. approach a legal strategist early in the innovation process Businesses, including startups, can’t afford to delay any longer. The first to file for a patent will own that innovation. Trends predict that dominance in AI will be determined not by who can innovate fastest, but who can protect their IP first. Conclusion Artificial intelligence may eliminate some jobs but it will also create new ones, and work that is done by humans will be more thoughtful, rewarding and fulfilling. AI will make us beyond human — in effect, superhuman. We’ll march on and evolve because that’s what we do. And we’re good at it.

f5 Reasons AI Won’t Replace Humans… It Will Make Us Superhuman

280 Stories To Learn About Future Of Ai

We live in a rapidly evolving world, and technological innovation keeps pushing the boundary of what we think is possible. Artificial Intelligence and Blockchain technology remain one of the biggest technological leaps of the last few decades; little wonder why it’s the most talked about topic today. AI, in simple terms, refers to the stimulation of human intelligence by computer systems to perform a specific task, while Blockchain is a safe and decentralized digital ledger used for transactions securely. So, what happens when these two cutting-edge technologies intersect? The answer is a world of new opportunities. Follow me as I explain how. Understanding AI AI is no longer a futuristic concept seen in sci-fi movies or imagined only by the wildest minds. It is now a reality influencing how we live, work, and interact. From getting personalized and helpful answers from voice-activated virtual assistants like Siri and Alexa to answering inquiries using chatbox. AI keeps making our lives easier and better, and it even gets better as they are quite accessible. But AI is not just limited to consumer-facing applications. It also finds tremendous , finance, and logistics industries. application in the healthcare Where they help to automate tasks and make decision-making more efficient. Understanding Blockchain Blockchain, on the other hand, is all about decentralization, security, and transparency. It , where no central authority can directly influence or control the ledger. operates on a decentralized network It currently finds wide use cases in DeFi and smart contracts, but there is more to what it can do. Because of its safety, low risk, and inability to be directly manipulated by a central authority, blockchain is an ideal technology for securely recording transactions in industries where trust and safety are critical such as finance and supply chain management. The Intersection of AI and Blockchain Now, let's talk about the magic that happens when AI and Blockchain intersect. Combining these two technological masterpieces can help organizations achieve even more advanced and secure solutions that can further improve our quality of life. Artificial intelligence can be used to analyze the large amounts of data generated on the Blockchain, which makes it easier for organizations to make more informed decisions. Furthermore, the decentralized nature of Blockchain provides a secure platform for AI algorithms to make predictions and decisions. The benefits of combining AI and Blockchain include increased efficiency, improved data accuracy, and enhanced security. For example, AI and Blockchain can in the financial industry. automate and secure complex financial transactions In the , they can be used to securely store and analyze patient data, improving the quality of patient care. There are tens of other uses case for AI and blockchain, some of which include: healthcare industry Decentralized AI applications: AI applications that run on a blockchain can offer greater transparency, security, and accountability than traditional or centralized AI systems. This makes it easier for organizations to share and access data for AI training while protecting sensitive information. Predictive analytics: Blockchain technology with AI algorithms can improve predictive analysis. Blockchain provides a secure and tamper-proof ecosystem which is important for an AI algorithm to give an accurate result. Blockchain improves trust and reduces the chance of a data breach since data can be stored and shared across multiple nodes. We get a secure and more efficient predictive analysis. Cybersecurity: It is no news now the blockchain mechanism makes it very hard for hackers to corrupt or manipulate the system, which is why it has a good use case in industries where security is important. And it only gets better as AI can quickly identify and flag potential threats and suspicious activity in real-time, allowing for the detection of any signs of fraud and flagging or blocking any transactions that appear suspicious. A popular example of brands using blockchain and AI for cybersecurity is Cognida. The platform uses AI algorithms to identify potential security threats and protect data privacy. At the same time, its decentralized architecture eliminates the need for centralized data storage, making it more difficult for cybercriminals to compromise the system. Supply chain management: The supply chain management industry has several problems that can be easily addressed by incorporating blockchain and Artificial intelligence. One of which is traceability. The lack of transparency in the supply chain can lead to logistics issues such as product recalls, fraud, and counterfeiting. But, the blockchain temper-proof ledger can easily help track products and its component, so they can move through the supply chain as fast as possible. AI algorithms can automate manual processes, reducing human error and improving the speed and accuracy of data exchange between supply chain partners. Blockchain can also provide a single source of truth for supply partner that can be accessed and shared in real-time, which improve transparency, trust, and business relation. AI and blockchain technology can improve supply chain management by providing a secure and transparent record of transactions and enabling organizations to automate supply chain processes using AI algorithms. Healthcare: Blockchain can provide a secure and decentralized platform for storing . Electronic Health Records (EHRs) AI algorithms can then analyze the data stored in the blockchain to identify patterns and personalize treatment plans, thereby improving patient outcomes. The two technological masterpieces also find good use cases in medicine supply chain systems and fraud detection. Challenges and Limitations It's important to note while AI and Blockchain have a lot of advantages, it is not without their challenges. Integration and interoperability are top of the list, as organizations may struggle to integrate AI and Blockchain solutions with existing systems. Ethical considerations must also be considered, as AI algorithms are sometimes biased and can discriminate if not properly designed and monitored. There are a few more challenges and limitations with the use of AI and blockchain, including: Scalability: Both AI and blockchain technologies require large amounts of data processing, which can result in scalability issues. This can cause the system to slow down or even crash when there are many transactions or computations. Regulation: There is a lack of a clear regulatory framework for AI and blockchain, which can make it difficult for organizations to use these technologies in a manner that complies with legal requirements. Complexity: AI and blockchain technologies require a high level of technical expertise, making maintenance and implementation complex. Costs: Integrating AI and blockchain technologies can be expensive since it is a significant investment in new and improved hardware, software, and skilled personnel. Despite these challenges and limitations, the potential benefits of combining AI and blockchain technology still outweighs the demerit, and the integration is likely to become more widespread in the coming years. Future Possibilities Despite the challenges listed above, the intersection of AI and Blockchain still has the potential to revolutionize industries and change the world as we know it. We can expect to see even more innovative solutions emerge as these technologies continue to evolve. For example, we could see the use of AI and Blockchain in smart cities, and the Internet of Things (IoT), as integration will provide us with smarter and more connected environments. Conclusion In conclusion, AI and Blockchain are two of the most exciting technologies of the last few decades, and their intersection has the potential to create new opportunities and change the way we live and work. Whether it's improving the efficiency of financial transactions, enhancing patient care, or creating smarter cities, the possibilities are endless. So buckle up, it's going to be a wild ride! Featured image by rawpixel.com on Freepik

AI and Blockchain: How These Technologies Are Creating New Opportunities

The 2021 AI Rewind: HackerNoon Edition

Transhumanism — Ghost Philosophy of a Future Age Transhumanism is the new byword, popularized by the commercial ventures of Elon Musk and other futurists in the business world. What makes it so fascinating is that the technology — in some forms at least — is already here. All we need to do now is integrate it with humankind and then it’ll be a race to the top. But the top of what, exactly? We’ve seen all the movies, haven’t we? and 2018’s . Human augmentation. Technology creating the potential in us to be superhuman. To go beyond the capabilities of what we think, as , is possible. AI: Artificial Intelligence , I, Robot Upgrade Homo sapiens sapiens The naysayers of this position — Creationists from the world’s organized religions as well as people with a conservative bent, go against the technological advancements in AI like they’re vampires to cloves of garlic. What we don’t know we fear. Nobody can blame them. For who knows what the future will bring from those with sprightly enough minds to bring about a technological revolution anyway. Transhumanism is fast approaching whether we like it or not. Today, big businesses are pumping multiple billions into artificial intelligence (AI), not sure where it is heading yet excited by it nonetheless. The convergence of highly distinctive, yet advanced, technologies will create a monster that will be unrecognizable soon enough. And when that happens, our species will be so reliant on the innovations that we will, through a process of the merging of our neural networks to machine-based AI, become a unified phenomenon. Integrated, both physically and neurologically, as an operational entity. “Over time I think we will probably see a closer merger of biological intelligence and digital intelligence.” - Elon Musk Over the next two decades, humans will develop and evolve in parity to the technological innovations we have created. In all three ways: psychologically, physically and behaviourally, we shall be augmented and enhanced as a species based on our interdependence on our own technological advancements. A transhumanist person, perfect in every way. Photo by on Markus Spiske Unsplash This evolutionary change will, in time, have an influence on other areas of our lives like how we behave in society, in governance, our business relationships and traditional ethical value systems. In Stanislaw Lem’s , pilot Ijon Tichy’s Twenty-first Voyage tells the story of Although the story is just entertaining science fiction, it goes some way in recognizing and presenting what the potential technology has in creating a man who goes beyond the restraints of biological, as well as evolutionary, possibilities. The Star Diaries ‘a civilisation which has achieved total corporeal and mental plasticity after a thousand-year rule by automorphists’ Stanislaw Lem, science fiction writer. Source: WikiCommons The Augmentation Hypothesis In the future, human bodies will become stronger and more intelligent. We will exceed our current capabilities with implants and when wearable applications will become the norm. Exo-suits will give us Herculean strength that will allow us to achieve things we could only dream of in the past. We will be able to talk to a Korean in their native language with a language translator implanted in our ear and to take photos and record films with implants in our irises. Microchips in our brains will be connected to our neural networks which will then connect directly to prosthetic limbs or other external bionic applications to enhance our lives in diverse ways. The ability that AI will present to us to calculate millions of complex problems per second will make this dream a reality. Machine learning will give us superpowers that collaboratively with AI in partnership with brain-machine interfaces (BMI), sometimes called mind-machine interfaces (MMI) as well as a few other terms, can open up channels never seen before. But something awry lies below the surface. Many are afraid the advances of AI and other forms of technological innovations will supersede the need for humans one day. That the human role in society will be ephemeral and eventually be controlled by robots. A transhumanist stance to this is seen by Paul Daugherty, Accenture’s Chief Technology and Innovation Officer, who believes the preponderance of AI in our lives will create jobs for humans in the areas of ‘Trainers, Explainers and Sustainers’. Light at the end of the tunnel, then. Speedy Thought Processes Currently, big businesses such as Facebook and are developing brain-machine interfaces that will effectively change communication between humans. Language discourses, and the way we use these communicative operations, are at this time circumscribed by a number of factors including how fast we can talk and the number of words we have at our disposal at any one time. This is the same with writing freehand or typing on a computer: There are only so many words we can write and type in a second/minute. Humans physically have a limit they cannot surpass. However, BMIs will be able to change this and give us more speed and accuracy in a number of cognitive areas: Neuralink BMIs could: enhance the ‘internal cognitive mechanics’, by that how our memory functions by better organizing the encoded data that travels to our brains through empirical as well as sensory experiences, then storing it systematically for easy-flow retrieval improve a human’s ‘outward cognitive mechanics’ of the basic communicative tools with ‘hybrid thinking’, as espoused by Ray Kurzweil, who believes the collaboration of human and cyber intelligence will lead to a greater linguistic capability enhancement of how we are understood in the future by not only other humans but by machine intelligence too. This is already realized partly with the advent of Microsoft’s Cortana, Apple’s Alexa and other first-generation chatbots with the two-way communication between machine and user revamp our sensory modalities of smell and touch with the use of biosensor implants connected between the neural networks of human and AI applications boost our interpretation and cognitive functions in relationship to multi-dimensional patterns in time and space, which could, if applied correctly, grant us the ability, for example, to 360-degree vision give us — though this is an obvious advantage of a successful implantation of a BMI system — enhanced thinking speed and problem-solving abilities The Empathy Revolution Virtual reality, and our adoption of it, will play a dominant role in the future when it allows us to empathize with others by giving us a unique perspective on how they live and behave. Humans’ neural pathways will be interlocked by BMIs to give us a unique perspective on the thinking and rationality of other people. This, it is hoped, will make us more susceptible to other people’s calamities, beliefs and value systems. And, if used correctly, could stop wars, suffering and other manmade maladies that seem all too common in the early 21st century. “Artificial intelligence is the science of making machines do things that would require intelligence if done by men” - Marvin Minsky Emotional intelligence, and the level an individual shows of it, could play a key role in how well a person responds to the outer phenomenological objects played out by the virtual world. People with a higher level of emotional intelligence would be — in theory at least — able to respond better to the signals given off by the object in their visual field of human behavioral traits such as breathing patterns, tone of voice and eye contact to name a few. Napalm victim during the Vietnam War. We have become too desensitized to war. Maybe experiencing it through VR will bring us closer to the victims’ own lives. Source: Wikipeida Giving people the chance to endure — say a battle and all its terrible consequences — through the technology of VR, could create in them a sense of empathy to the virtual experience they have undergone, which is then hoped will change them as people in regard to their political beliefs and how they feel about their country’s warmongering tendencies. This could change a person’s individual opinion on their nation’s foreign policies, attitude to refugees and how they view and spend money. Business, Business, Business Following on from money, futurists believe AI will develop the industrial sphere with smart factories becoming the norm. People will collaborate with their AI counterparts to enhance their productivity ratio and offer advice on work performance, as well as AI giving one-to-one-based training and guidance in any area of an individual’s personal goals and performance. In the boardroom, too, there will be a shift from human leadership when directors and managers are partly replaced by AI for certain functions. Advanced machine learning in the coming decades will also make it easier via complex algorithms to retroactively study and analyse past use cases and historical statistics from market trends and use them for future predictions. This will be compounded by the application of more advanced machines in the form of quantum computers. Humanity’s Transhumanist Final Destination Freidrich Nietzche philosophy of the Superman may soon be here. The technological enhancement of our bodies is not a new theory. To improve upon ourselves is just human nature and has been a known goal for centuries. Übermensch “It is their belief that we can and should eradicate ageing as a cause of death; that we can and should use technology to augment our bodies and our minds; that we can and should merge with machines, remaking ourselves, finally, in the image of our own higher ideals.” — Mark O’Connell, author of ‘To Be a Machine : Encounters With a Post-Human Future ’ To do this we are creating for ourselves a better life, at least materially speaking. By merging our bodies, that is the biological and anatomical parts to bionic/robotic applications, we will by default be creating a being with greater physical strength and vastly more intelligence. Not to mention an extended life span, that if aligned with the life cycle of the machines we will be integrated into, could see us reach incalculable ages. It’s a pity Michael Jackson won’t be around to see that! However, do we really want to go in this direction? The benefits of such an approach to our future could, for obvious reasons, be astronomical in regard to human development and the way we will be able to control and understand our environment. Yet, from this there come the dilemmas, both in the ethical and evolutionary spheres. Such transhumanist dreams of a more developed human being are all fine and dandy when we’re talking about old people, mentally disabled or the infirmed, extending their lives or, at the very least, making them feel more comfortable in their predicament, but what with the rest of us: the young, the strong, the intelligent Harvard graduate with no health problems and certainly no mental disorders? What then? Do we just improve on something that is not broken? Do we believe this will make us better human beings? Many do. With proponents of transhumanism getting their way, Usain Bolt’s ten-year-old 100-metre world record of 9.58 seconds will not be a record for very much longer. Bionic people— with either carbon-fiber implants or some other dazzling feat of technological innovation like Musk’s idea of : neural lace “…you have your limbic system, the cortex, and then a digital layer, sort of a third layer above the cortex that could work well and symbiotically with you… Some sort of interface with your cortical neurons… A complete roadway to all of your neurons.” Exciting and scary in equal measure. Over the next few years, things will be escalating in the technological realm like never before. So, strap yourselves in folks, because where we’re going we don’t need roads! Maybe one day we will have 360-degree vision. Photo by on Liam Charmer Unsplash <a href="https://medium.com/media/3c851dac986ab6dbb2d1aaa91205a8eb/href">https://medium.com/media/3c851dac986ab6dbb2d1aaa91205a8eb/href</a>

FAST AI Movies

fast-ai-movies.de

-- employees

Since n.d.

COMPANY RANKING

FAST AI MOVIES

EVERGREEN INDEX #3866

FAST AI Movies WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

FAST AI Movies

fast-ai-movies.de

-- employees

Since n.d.

COMPANY RANKING

FAST AI MOVIES

EVERGREEN INDEX #3866

RELATED COMPANIESRANK

STORIES ABOUT FAST AI MOVIES

FAST AI Movies WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!