Artificial intelligence is rapidly changing many aspects of how we work and live. (How many stories did you read last week about self-driving cars and job-stealing robots? Perhaps your holiday shopping involved some AI algorithms, as well.) But despite the constant flow of news, many misconceptions about AI remain.
AI doesn’t think in our sense of the word at all, Scriffignano explains. “In many ways, it’s not really intelligence. It’s regressive.”
IT leaders should make deliberate choices about what AI can and can’t do on its own. “You have to pay attention to giving AI autonomy intentionally and not by accident,”
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Tomi Engdahl says:
World’s most valuable AI startup SenseTime unveils self-driving center in Japan
https://techcrunch.com/2019/01/10/sensetime-self-driving-center-japan/?sr_share=facebook&utm_source=tcfbpage
Tomi Engdahl says:
A New Approach to Understanding How Machines Think
https://www.quantamagazine.org/been-kim-is-building-a-translator-for-artificial-intelligence-20190110/
Neural networks are famously incomprehensible — a computer can come up with a good answer, but not be able to explain what led to the conclusion. Been Kim is developing a “translator for humans” so that we can understand when artificial intelligence breaks down.
Tomi Engdahl says:
Researchers Use Deep Learning to Convert Mono Sounds to 3D
https://blog.hackster.io/researchers-use-deep-learning-to-convert-mono-sounds-to-3d-a1ff684e4585
Tomi Engdahl says:
THE NEURAL NETWORK ZOO
http://www.asimovinstitute.org/neural-network-zoo/
With new neural network architectures popping up every now and then, it’s hard to keep track of them all. Knowing all the abbreviations being thrown around (DCIGN, BiLSTM, DCGAN, anyone?) can be a bit overwhelming at first.
So I decided to compose a cheat sheet containing many of those architectures
Tomi Engdahl says:
Katrina Brooker / Fast Company:
A behind-the-scenes look at Masayoshi Son’s investment strategy, which is driven by the belief that computers will run the planet more intelligently than humans
The most powerful person in Silicon Valley
https://www.fastcompany.com/90285552/the-most-powerful-person-in-silicon-valley
Billionaire Masayoshi Son–not Elon Musk, Jeff Bezos, or Mark Zuckerberg–has the most audacious vision for an AI-powered utopia where machines control how we live. And he’s spending hundreds of billions of dollars to realize it. Are you ready to live in Masa World?
Tomi Engdahl says:
https://www.uusiteknologia.fi/2019/01/15/suomi-on-17-tekoalyjulkaisuissa-uusi-selvitys/
Tekoälyn tutkimusosaaminen on Valtioneuvoston teettämän selvityksen mukaan tieteellisten julkaisujen perusteella Suomessa verrattain hyvätasoista. Olemme sijalla 17 Etelä-Korean ja Itävallan välissä. Suomen osuus maailman tekoälyjulkaisujen määrästä on vain puoli prosenttia.
Tomi Engdahl says:
Tekoäly vaatii Suomessa nyt pikaisia toimia
http://www.etn.fi/index.php/13-news/8936-tekoaly-vaatii-suomessa-nyt-pikaisia-toimia
Tomi Engdahl says:
Tekoälyn kokonaiskuva ja kansallinen osaamiskartoitus – loppuraportti
https://www.vtt.fi/Documents/uutiset/4_2019_Tekoalyn_kokonaiskuva.pdf
Tomi Engdahl says:
MicroZed Chronicles: Deephi DNNDK — Deep Learning SDK
https://blog.hackster.io/microzed-chronicles-deephi-dnndk-deep-learning-sdk-d35baeaaee
For those working in machine learning / artificial intelligence, Xilinx’s acquisition of Deephi was rather exciting. Deephi’s technology significantly simplifies the acceleration of deep neural networks in heterogeneous SoCs like the Zynq and Zynq MPSoC.
Tomi Engdahl says:
Hardware Mathematics for Artificial Intelligence
https://semiengineering.com/hardware-mathematics-for-artificial-intelligence/
Why math and a library of mathematical IP cores is important for AI.
Tomi Engdahl says:
Predictive Maintenance Can Benefit All Manufacturers
https://www.designnews.com/industrial-machinery/predictive-maintenance-can-benefit-all-manufacturers/64099930860063?ADTRK=UBM&elq_mid=7109&elq_cid=876648
With machine learning and artificial intelligence, manufacturers can eliminate maintenance guesswork and minimize unplanned machine downtime.
Tomi Engdahl says:
Five Steps to TensorFlow on the Raspberry Pi
https://hackaday.com/2018/05/18/five-steps-to-tensorflow-on-the-raspberry-pi/
Tomi Engdahl says:
https://hackaday.com/2018/05/22/machine-learning-crash-course-from-google/
Tomi Engdahl says:
Using TensorFlow To Recognize Your Own Objects
https://hackaday.com/2018/05/23/using-tensorflow-to-recognize-your-own-objects/
Tomi Engdahl says:
Stock Market Prediction With Natural Language Machine Learning
https://hackaday.com/2018/05/30/stock-market-prediction-with-natural-language-machine-learning/
Tomi Engdahl says:
Facebook’s Universal Music Translator
https://hackaday.com/2018/06/02/facebooks-universal-music-translator/
Tomi Engdahl says:
https://hackaday.com/2018/06/21/make-a-natural-language-phone-bot-like-googles-duplex-ai/
Tomi Engdahl says:
https://hackaday.com/2018/07/03/disneys-new-robot-limbs-trained-using-neural-networks/
Tomi Engdahl says:
https://hackaday.com/2018/07/02/using-an-ai-and-wifi-to-see-through-walls/
Tomi Engdahl says:
https://hackaday.com/2018/07/06/solar-pi-cluster-scours-internet-for-nudes/
Tomi Engdahl says:
Inside Facebook, Twitter and Google’s AI battle over your social lives
https://www.cnet.com/news/inside-facebook-twitter-and-googles-ai-battle-over-your-social-lives/
Tomi Engdahl says:
Deep neural network on arduino – MNIST handwritten
https://hackaday.io/project/41159-deep-neural-network-on-arduino-mnist-handwritten
170 neurons running on arduino can recognize MNIST digits with 97% accuracy
Tomi Engdahl says:
The Next Semiconductor Revolution
https://semiengineering.com/the-next-semiconductor-revolution/
Four industry experts talk about what’s changing, how quickly, and where the limits are with AI.
What will drive the next semiconductor revolution?
When you ask people with decades of experience in semiconductor manufacturing and software development, the answers include everything from AI and materials to neuromorphic architectures.
Tomi Engdahl says:
http://www.etn.fi/index.php/13-news/8936-tekoaly-vaatii-suomessa-nyt-pikaisia-toimia
Tomi Engdahl says:
The most powerful person in Silicon Valley
https://www.fastcompany.com/90285552/the-most-powerful-person-in-silicon-valley
Billionaire Masayoshi Son–not Elon Musk, Jeff Bezos, or Mark Zuckerberg–has the most audacious vision for an AI-powered utopia where machines control how we live. And he’s spending hundreds of billions of dollars to realize it. Are you ready to live in Masa World?
Tomi Engdahl says:
Tom Simonite / Wired:
Strategy Robot, founded by the creators of an AI bot that beat four top professional Texas Hold ‘Em players, signs a $10M two-year contract with the US Army
A Poker-Playing Robot Goes to Work for the Pentagon
https://www.wired.com/story/poker-playing-robot-goes-to-pentagon/
In 2017, a poker bot called Libratus made headlines when it roundly defeated four top human players at no-limit Texas Hold ‘Em. Now, Libratus’ technology is being adapted to take on opponents of a different kind—in service of the US military.
Libratus—Latin for balanced—was created by researchers from Carnegie Mellon University to test ideas for automated decisionmaking based on game theory. Early last year, the professor who led the project, Tuomas Sandholm, founded a startup called Strategy Robot to adapt his lab’s game-playing technology for government use, such as in war games and simulations used to explore military strategy and planning. Late in August, public records show, the company received a two-year contract of up to $10 million with the US Army.
Tomi Engdahl says:
Intelin tekoälytikku verkosta satasella
http://etn.fi/index.php?option=com_content&view=article&id=8970&via=n&datum=2019-01-22_15:28:09&mottagare=30929
Tomi Engdahl says:
http://www.etn.fi/index.php/13-news/8970-intelin-tekoalytikku-verkosta-satasella
https://www.rutronik24.com/product/intel/ncsm2485.dk/11144795.html
Tomi Engdahl says:
World Economic Forum warns of AI’s potential to worsen global inequality
https://techcrunch.com/2019/01/23/world-economic-forum-warns-of-ais-potential-to-worsen-global-inequality/?sr_share=facebook&utm_source=tcfbpage
Tech and political leaders sounded the alarm bell today about the potential for artificial intelligence to exacerbate huge inequalities across the world. The mood music coming out of the World Economic Forum is that AI is seen as having great potential to solve some of the world’s most pressing issues (such as climate change), but if individual organizations and countries implement AI systems and others do not, then they will race far ahead, spreading inequality between economies and leading to unforeseen consequences for the planet.
Tomi Engdahl says:
DESTROYING Piano Tiles with an Auto clicker
https://www.youtube.com/watch?v=wHRubMACen0
I write an AI to play piano tiles and its pretty good
Huge thanks to Brilliant.org for supporting this channel, check them out at https://brilliant.org/codebullet
Tomi Engdahl says:
Kyle Wiggers / VentureBeat:
Alexa AI scientists describe in a paper a technique that uses millions of unannotated interactions with Amazon’s voice assistant to reduce NLP error rate by 8%
Amazon team taps millions of Alexa interactions to reduce NLP error rate
https://venturebeat.com/2019/01/22/amazon-team-taps-millions-of-alexa-interactions-to-reduce-nlp-error-rate/
Tomi Engdahl says:
AI That Creates AI
https://www.youtube.com/watch?v=hVv68aHYSs4
How can we build AI that creates AI? This concept actually already exists! Google uses self-creating AI as part of its AutoML service that finds the best model for customers. Genetic algorithms and neuroevolutionary strategies offer us a way to replicate the process of natural selection en silico. I’ll talk about ways of using machine learning algorithms to create better machine learning algorithms in this video.
This is the code for “AI that Creates AI” By Siraj Raval on Youtube
https://github.com/llSourcell/neuroevolution-for-flappy-birds
Tomi Engdahl says:
Flex Logix Unveils Fast Neural Inferencing Engine
https://www.eeweb.com/profile/eeweb/news/flex-logix-unveils-fast-neural-inferencing-engine
NMAX, a neural inferencing engine from Flex Logix, provides inferencing throughput from 1 to over 100 TOPS with high MAC utilization even for a batch size of 1, a critical requirement of edge applications. According to Flex Logix, NMAX achieves this performance at a much lower cost and with much less power consumption than competitive solutions. For example, NMAX attains data-center class performance with just one or two LPDDR4 DRAMs, compared to eight or more for other solutions. It also leverages the company’s interconnect technologies developed for eFPGA.
Tomi Engdahl says:
Tom Krazit / GeekWire:
AWS launches Neo-AI, an open source project for ML training models to be run across multiple operating environments, under the Apache Software License — Amazon Web Services has decided to release the code behind one of its key machine-learning services as an open-source project …
Amazon Web Services continues open-source push with code behind SageMaker Neo
https://www.geekwire.com/2019/amazon-web-services-continues-open-source-push-code-behind-sagemaker-neo/
Tomi Engdahl says:
4 Experiments Where the AI Outsmarted Its Creators
https://www.youtube.com/watch?v=GdTBqBnqhaQ
The paper “The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities” is available here:
https://arxiv.org/abs/1803.03453
Tomi Engdahl says:
YOLO Object Detection (TensorFlow tutorial)
https://www.youtube.com/watch?v=4eIBisqx9_g
You Only Look Once – this object detection algorithm is currently the state of the art, outperforming R-CNN and it’s variants. I’ll go into some different object detection algorithm improvements over the years, then dive into YOLO theory and a programmatic implementation using Tensorflow!
Code for this video:
https://github.com/llSourcell/YOLO_Object_Detection
Tomi Engdahl says:
How computers learn to recognize objects instantly | Joseph Redmon
https://www.youtube.com/watch?v=Cgxsv1riJhI
Ten years ago, researchers thought that getting a computer to tell the difference between a cat and a dog would be almost impossible. Today, computer vision systems do it with greater than 99 percent accuracy. How? Joseph Redmon works on the YOLO (You Only Look Once) system, an open-source method of object detection that can identify objects in images and video — from zebras to stop signs — with lightning-quick speed. In a remarkable live demo, Redmon shows off this important step forward for applications like self-driving cars, robotics and even cancer detection.
Tomi Engdahl says:
AI Codes its Own ‘AI Child’ – Artificial Intelligence breakthrough!
https://www.youtube.com/watch?v=YNLC0wJSHxI
Tomi Engdahl says:
The Real Reason to be Afraid of Artificial Intelligence | Peter Haas | TEDxDirigo
https://www.youtube.com/watch?v=TRzBk_KuIaM
A robotics researcher afraid of robots, Peter Haas, invites us into his world of understand where the threats of robots and artificial intelligence lie. Before we get to Sci-Fi robot death machines, there’s something right in front of us we need to confront – ourselves. Peter is the Associate Director of the Brown University Humanity Centered Robotics Initiative.
Tomi Engdahl says:
DeepMind’s AI agents conquer human pros at Starcraft II
But the humans won a single match, leaving room for improvement on both sides
https://www.theverge.com/2019/1/24/18196135/google-deepmind-ai-starcraft-2-victory
AI agents developed by Google’s DeepMind subsidiary have beaten human pros at Starcraft II — a first in the world of artificial intelligence. In a series of matches streamed on YouTube and Twitch, AI players beat the humans 10 games in a row. In the final match, pro player Grzegorz “MaNa” Komincz was able to snatch a single victory for humanity.
“The history of AI has been marked by a number of significant benchmark victories in different games,”
Tomi Engdahl says:
Intel debuts Nauta for distributed deep learning with Kubernetes
https://venturebeat.com/2019/01/23/intel-debuts-nauta-for-distributed-deep-learning-with-kubernetes/
Intel today announced the open source release of Nauta, a platform for deep learning distributed across multiple servers using Kubernetes or Docker.
The platform can operate with a number of popular machine learning frameworks such as MXNet, TensorFlow, and PyTorch, and uses processing systems that can work with a cluster of Intel’s Xeon CPUs.
https://github.com/intelAI/Nauta
Tomi Engdahl says:
https://knowm.org/a-brief-history-of-neuromorphic-computing/?fbclid=IwAR3OlVeifCJOAJVLNmximpBwU42NaZcfAnAtfiLUsjJpg5HW2_WHu7K5mR8
Tomi Engdahl says:
To cripple AI, hackers are turning data against itself
https://www.wired.co.uk/article/artificial-intelligence-hacking-machine-learning-adversarial
Data has powered the artificial intelligence revolution. Now security experts are uncovering worrying ways in which AIs can be hacked to go rogue
Tomi Engdahl says:
The AI market is growing, but how quickly is tough to pin down
https://techcrunch.com/2019/01/20/the-ai-market-is-growing-but-how-quickly-is-tough-to-pin-down/?utm_source=tcfbpage&sr_share=facebook
Tomi Engdahl says:
RoadBotics’ AI Could Change the Way Cities Maintain Roads
https://spectrum.ieee.org/cars-that-think/transportation/sensors/roadbotics-ai-could-change-the-way-cities-maintain-roads
Tomi Engdahl says:
AI Software Learns to Make AI Software
https://www.technologyreview.com/s/603381/ai-software-learns-to-make-ai-software/?utm_campaign=Technology+Review&utm_source=facebook.com&utm_medium=social
Google and others think software that learns to learn could take over some work done by AI experts.
Tomi Engdahl says:
Chemical Computing, the Future of Artificial Intelligence
https://www.bbvaopenmind.com/en/chemical-computing-the-future-of-artificial-intelligence/?utm_source=facebook&utm_medium=techreview&utm_campaign=MITcompany&cid=soc:oth:fb:—-mitcompany::::::::sitlnk:techreview:
the foundation stone of a new discipline: chemical computing. This technological path is an alternative to quantum computing and conventional computing, capable of processing in parallel based on the same operating principles as our brain, promising futuristic applications, such as integrating in our body in the form of intelligent biosensors.
Tomi Engdahl says:
DeepMind’s AI agents conquer human pros at Starcraft II
https://www.theverge.com/2019/1/24/18196135/google-deepmind-ai-starcraft-2-victory
But the humans won a single match, leaving room for improvement on both sides
Tomi Engdahl says:
Cate Cadell / Reuters:
Inside Alibaba’s futuristic 290-room FlyZoo hotel where it showcases its prowess in AI and incubates tech it wants to sell to the hospitality industry — HANGZHOU, China (Reuters) – Gliding silently through Alibaba Group Holding Ltd’s futuristic “FlyZoo” hotel, black disc-shaped robots …
At Alibaba’s futuristic hotel, robots deliver towels and mix cocktails
https://www.reuters.com/article/us-alibaba-hotels-robots/at-alibabas-futuristic-hotel-robots-deliver-towels-and-mix-cocktails-idUSKCN1PG21W
Tomi Engdahl says:
It’s All About The Data
https://semiengineering.com/its-all-about-the-data-2/
From AI to Moore’s Law, the entire industry is deep in the throes of massive changes.
The entire tech industry has changed in several fundamental ways over the past year due to the massive growth in data.
Individually, those changes are significant. Taken together, those changes will have a massive impact on the chip industry for the foreseeable future.
The obvious shift is the infusion of AI (and its subcategories, machine learning and deep learning) into different markets. Chips are now being built specifically to accelerate AI algorithms. In addition, AI is being used to improve and streamline the design and development of those chips and other technologies.