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:
Machine Learning Detects Distracted Politicians
https://hackaday.com/2022/01/17/machine-learning-detects-distracted-politicians/
Dries Depoorter] has a knack for highly technical projects with a solid artistic bent to them, and this piece is no exception. The Flemish Scrollers is a software system that watches live streamed sessions of the Flemish government, and uses Python and machine learning to identify and highlight politicians who pull out phones and start scrolling. The results? Pushed out live on Twitter and Instagram, naturally. The project started back in July 2021, and has been dutifully running ever since, so by now we expect that holding one’s phone where the camera can see it is probably considered a rookie mistake.
This project can also be considered a good example of how to properly handle confidence in results depending on the application. In this case, false negatives (a politician is using a phone, but the software doesn’t detect it properly) are much more acceptable than false positives (a member gets incorrectly identified, or is wrongly called-out for using a mobile device when they are not.)
https://driesdepoorter.be/theflemishscrollers/
Tomi Engdahl says:
AI Camera Knows Its S**t
https://hackaday.com/2022/01/17/ai-camera-knows-its-st/
[Caleb] shares a problem with most dog owners. Dogs leave their… byproducts…all over your yard. Some people pick it up right away and some just leave it. But what if your dog has run of the yard? How do you know where these piles are hiding? A security camera and AI image detection is the answer, but probably not the way that you think.
You might think as we did that you could train the system to recognize the–um–piles. But instead, [Caleb] elected to have the AI do animal pose estimation to detect the dog’s posture while producing the target. This is probably easier than recognizing a nondescript pile and then it doesn’t matter if it is, say, covered with snow.
Building an AI Dog Poop Detector for my Backyard
https://www.youtube.com/watch?v=uWZu3rnj-kQ&t=2s
Tomi Engdahl says:
A First: An AI System Has Been Named An Inventor A patent was granted that lists it as the creator of a food container
https://spectrum.ieee.org/first-time-ai-named-inventor
The South African patent office made history in July when it issued a patent that listed an artificial intelligence system as the inventor.
The patent is for a food container that uses fractal designs to create pits and bulges in its sides. Designed for the packaging industry, the new configuration allows containers to fit more tightly together so they can be transported better. The shape also makes it easier for robotic arms to pick up the containers.
The patent’s owner, AI pioneer Stephen L. Thaler, created the inventor, the AI system known as Dabus (device for the autonomous bootstrapping of unified sentience).
The patent success in South Africa was thanks to Thaler’s attorney, Ryan Abbott.
Abbott and his team filed applications in 2018 and 2019 in 17 patent offices around the world, including in the United States, several European countries, China, Japan, and India.
The European Patent Office (EPO), the U.K. Intellectual Property Office (UKIPO), the U.S. Patent and Trademark Office (USPTO), and Intellectual Property (IP) Australia all denied the application, but Abbott filed appeals. He won an appeal in August, when the Federal Court of Australia ruled that the AI system can be an inventor under the country’s 1990 Patents Act.
“Some of the time, the AI is automating the sort of activity that makes a human being an inventor on a patent,” he says. “It occurred to me that this sort of thing was likely to become far more prevalent in the future, and that it had some significant implications for research and development.”
Some patent applicants have been instructed by their attorney to use a person’s name on the patent even if a machine came up with the invention.
But Abbott says that’s a “short-sighted approach.” If a lawsuit is filed challenging a patent, the listed inventor could be deposed as part of the proceedings. If that person couldn’t prove he or she was the inventor, the patent couldn’t be enforced. Abbott acknowledges that most patents are never litigated, but he says it still is a concern for him.
Tomi Engdahl says:
IMPACT ON INVENTORS
Abbott says he believes the decisions in Australia and South Africa will encourage people to build and use machines that can generate inventive output and use them in research and development. That would in turn, he says, promote the commercialization of new technologies.
Tomi Engdahl says:
https://www.edn.com/autonomous-mobile-robot-amr-design-revisited-with-ai-algorithms/
Tomi Engdahl says:
Keith Romer / New York Times:
AI tools can generate an optimal poker strategy, balancing bluffing and playing it straight, which some professional players are using to augment their play
How A.I. Conquered Poker
Good poker players have always known that they need to
https://www.nytimes.com/2022/01/18/magazine/ai-technology-poker.html
Tomi Engdahl says:
Madhumita Murgia / Financial Times:
Survey finds that 76% of Chinese citizens and 68% of Indians say they trust AI companies compared to only 35% in France, the UK, and the US — For many outside the tech world, “data” means soulless numbers. Perhaps it causes their eyes to glaze over with boredom.
https://www.ft.com/content/e3f36d82-89b8-41df-ae11-0653ce7e7944
Tomi Engdahl says:
A Machine Learning Algorithm for Collaborative Push-and-Shove Boosts Robots Grasping Accuracy
By breaking a pile of objects apart with a few careful shoves, a robot arm’s ability to grasp objects goes from 35 percent to 97 percent.
https://www.hackster.io/news/a-machine-learning-algorithm-for-collaborative-push-and-shove-boosts-robots-grasping-accuracy-205ca1268bca
Tomi Engdahl says:
New technique guides humans when to trust an AI
A method to help workers collaborate with artificial intelligence systems.
https://www.techexplorist.com/new-technique-guides-humans-trust-ai/44203/
Tomi Engdahl says:
James Cameron: Skynet Would Destroy Humanity With Deepfakes, Not Nukes
The Terminator director warns about the dangers of disinformation and AI-generated phony videos.
https://uk.pcmag.com/social-media/138318/james-cameron-skynet-would-destroy-humanity-with-deepfakes-not-nukes
If machines ever rise up to overthrow humanity, expect them to use deepfakes, not nukes, to take down our society, says James Cameron, the filmmaker behind the Terminator franchise.
“All Skynet would have to do is just deepfake a bunch of people, pit them against each other, stir up a lot of foment, and just run this giant deepfake on humanity,” Cameron told The BBC in an interview last week.
He brought up the topic while discussing the threat of AI-generated “deepfake” videos, which can manipulate someone’s face to say something else. Cameron fears the same technology could be abused to cause political chaos or start a war.
If Skynet ever emerges in our world, Cameron thinks the evil AI could plot humanity’s downfall rather easily by creating seemingly realistic, but ultimately fake videos, to fool people into hating one another. “It would actually look a lot like what’s going on right now,” he said, alluding to how disinformation and conspiracy theories can easily go viral in our digital age.
Cameron added that deepfakes exploit how video evidence can often convince us something is true.
“This is the great problem with us relying on video. The news cycles happen so fast, and people respond so quickly, you could have a major incident take place between the interval between when the deepfake drops and when it’s exposed as a fake,” he said.
Tomi Engdahl says:
Meta says its new AI supercomputer will be the world’s fastest by mid-2022
It’s using the AI Research SuperCluster to develop new experiences for the metaverse.
https://www.engadget.com/meta-ai-supercomputer-worlds-fastest-rsc-184644623.html
Tomi Engdahl says:
The Human Side of Computing
If you’re happy and you know it, then your face will surely show it, and this novel light-field camera and AI will classify it.
https://www.hackster.io/news/the-human-side-of-computing-b5771e7f7234
Tomi Engdahl says:
Meta Aims to Build the World’s Fastest AI Supercomputer The AI Research SuperCluster could help the company develop real-time voice translations
https://spectrum.ieee.org/meta-ai-supercomputer
Tomi Engdahl says:
Building value-chain resilience with AI
https://www.mckinsey.com/industries/metals-and-mining/our-insights/building-value-chain-resilience-with-ai
Value chains are facing increased uncertainty. A threefold approach underpinned by artificial intelligence can help companies adapt to rapidly changing markets and operational challenges.
Increasingly sophisticated artificial intelligence (AI) technologies—such as advanced analytics-based forecasting, digital-twin supply-chain simulations, and supply-chain optimization tools—can help companies improve the resilience-efficiency balance of their value chains. We
Tomi Engdahl says:
Skynet Wiping Out Humanity “Would Look A Lot Like What’s Going On Right Now” Says James Cameron
https://www.iflscience.com/technology/skynet-wiping-out-humanity-would-look-a-lot-like-whats-going-on-right-now-says-james-cameron/
In the 1984 movie Terminator, an artificially intelligent (AI) defense network called Skynet becomes self-aware and promptly starts a global nuclear war in order to wipe out humanity.
The film utilizes humanity’s biggest fears at the time: nuclear annihilation and a robot Arnold Schwarzenegger that’s been sent back in time. Our fears and ideas about artificial intelligence have changed somewhat in the last (oh god) 37 years, however – and the director of Terminator has given an update on how he thinks Skynet could feasibly take over the world, with no need to have access to a nuclear arsenal at all.
“If Skynet wanted to take over and wipe us out, it would actually look a lot like what’s going on right now,” Cameron said in the interview.
“It’s not going to have to wipe out the entire biosphere and environment with nuclear weapons to do it, it’s going to be so much easier and less energy required to just turn our minds against ourselves.”
Tomi Engdahl says:
The data science, machine learning and artificial intelligence (AI) markets are growing. When the importance of fast innovation and exploration is undeniable – how to ensure that investments remain value-creating and benefits scale up also in the future?
Data science and AI investments – How to increase business value and enhance change resilience?
https://www.solita.fi/en/blogs/data-science-and-ai-investments-how-to-increase-business-value-and-enhance-change-resilience/?utm_campaign=Finland%20Funnel%20Advertsing%20Campaign&utm_source=facebook&utm_medium=paidsocial&utm_term=traffic&utm_content=data-blog&hsa_acc=304727541562645&hsa_cam=23849462460180634&hsa_grp=23849462460200634&hsa_ad=23849462713580634&hsa_src=fb&hsa_net=facebook&hsa_ver=3
The data science, machine learning and artificial intelligence (AI) market keep on growing – no change in that. Companies are investing more and more in these capabilities to create value, either through growing existing or new businesses, increasing resource efficiency, or growing customer value.
Tomi Engdahl says:
https://www.electronicdesign.com/technologies/embedded-revolution/article/21213976/pcisig-how-pcie-tech-can-help-build-machinelearning-accelerators?utm_source=EG%20ED%20Connected%20Solutions&utm_medium=email&utm_campaign=CPS220124017&o_eid=7211D2691390C9R&rdx.ident%5Bpull%5D=omeda%7C7211D2691390C9R&oly_enc_id=7211D2691390C9R
Tomi Engdahl says:
ATI’s Radeon 8500: First GPU With Hardware Tessellation
Jan. 26, 2022
Graphics Chip Chronicles Vol. 7 No. 1 – ATI’s TruForm technology tessellated three-dimensional surfaces used existing triangles and tacked on additional triangles to them to add detail to a polygonal model.
https://www.electronicdesign.com/technologies/embedded-revolution/article/21213985/jon-peddie-research-atis-radeon-8500-first-gpu-with-hardware-tessellation
Tomi Engdahl says:
Study: Medical Image AIs Need a Good “Hallucination Map” Astute new algorithms identify false structures in brain scans
https://spectrum.ieee.org/ai-medical-imaging-false-structures?utm_campaign=RebelMouse&socialux=facebook&share_id=6883706&utm_medium=social&utm_content=IEEE+Spectrum&utm_source=facebook
Medical imaging techniques such as MRIs and CT scans have revolutionized the medical field—helping to advance novel therapies and provide hard data and new perspectives on the health of patients. Such non-invasive approaches allow doctors to peer into the brains and bodies of patients, detecting anything from fractured bones to brain tumors.
medical imaging devices do not record images directly. Instead, the raw data collected by the devices are analyzed by a computer, and machine learning algorithms are used to reconstruct the images that doctors and radiologists use for diagnosing a health complication. Image reconstruction is done based on the known physics of the imaging device, along with a set of assumptions about how the final image should appear.
“However, if certain assumptions are wrong during image reconstruction, false structures may be introduced into the final image,” explains Mark Anastasio, a professor of Bioengineering at the University of Illinois at Urbana–Champaign.
To address this issue, Anastasio and his colleagues have been working on a new technique that can identify when algorithms for image reconstruction are likely creating false structures. It works by mapping out errors in the reconstructed image that are not attributable to the raw image data.
Tomi Engdahl says:
NTU Researchers Create an ML Model, Ycogni, Capable of Screening Smartwatch Data for Depression
A low-cost, off-the-shelf Fitbit’s data proves capable of predicting its wearer’s likelihood for depressive symptoms.
https://www.hackster.io/news/ntu-researchers-create-an-ml-model-ycogni-capable-of-screening-smartwatch-data-for-depression-5299667959bf
Tomi Engdahl says:
Here’s What It Will Take to Reduce AI’s Carbon Footprint
https://www.eetimes.com/heres-what-it-will-take-to-reduce-ais-carbon-footprint/#
Following the conclusion of the COP26 climate conference, private companies and governments alike are stepping up their promises to combat climate change, bringing to bear a mix of public policy and innovative technologies to address one of our era’s defining challenges.
One such company is Nvidia, creators of a supercomputer (dubbed “Earth-2”) that leverages predictive models to help scientists understand how climatic shifts might manifest across the world in the coming decades. But as exciting as it may be to contemplate a world where AI helps tackle the climate crisis, there’s no escaping the bitter irony that AI itself comes with a significant carbon footprint.
Case in point: A single transformer-based neural network (213 million parameters) built using traditional neural architecture search creates more than 600,000 pounds of carbon dioxide, nearly six times the emissions that an average car produces in its lifetime.
Shrinking AI’s carbon footprint is only possible if we first understand the scope of the problem. Fortunately, there are steps tech industry leaders can take to ensure that AI innovation doesn’t come at the expense of the planet’s health. From rethinking hardware and the complexity of models to reducing processing required in both the training and inference stages, here’s what it will take to achieve eco-friendly AI innovation.
No to power-hungry models
AI models require vast amounts of energy to function, and their hunger for computing power grows along with model accuracy. The larger (and therefore typically more predictively accurate) an AI model is, the more energy it requires.
To put this massive energy consumption in context, in 2020, an algorithm used to solve a Rubik’s Cube required as much energy as three nuclear power plants produce in an hour. Although this example is an outlier (and AI models tend to focus on addressing more practical problems than simply solving Rubik’s Cubes), it still illustrates an overall trend: As AI models continue to grow in size and accuracy, so too does their negative impact on the environment.
To offer up a less whimsical statistic: As early as 2018, data centers that power inference used an estimated 200 terawatt-hours (TWh) each year, more than the national energy consumption of some countries.
Tomi Engdahl says:
DeepMind’s AlphaCode AI writes code at a competitive level
https://techcrunch.com/2022/02/02/deepminds-alphacode-ai-writes-code-at-a-competitive-level/?tpcc=tcplusfacebook
DeepMind has created an AI capable of writing code to solve arbitrary problems posed to it, as proven by participating in a coding challenge and placing — well, somewhere in the middle. It won’t be taking any software engineers’ jobs just yet, but it’s promising and may help automate basic tasks.
Tomi Engdahl says:
https://www.uusiteknologia.fi/2022/02/02/monikielinen-aaniohjauskortti-ja-ohjelmisto-myos-suomeksi/
Tomi Engdahl says:
Olen pitkään ollut kyllästynyt robotti-keskusteluun ja tämä Bayerischer Rundfunkin katsaus selvittää miksi kyse on pelkästään softasta. Ei ole robotteja ja GPT-3:kin voi toistaiseksi unohtaa. https://blogs.lse.ac.uk/polis/2022/02/03/can-ai-really-write-like-a-human/ Ja tekoälyhypetys on loppumassa myös finanssialalla, jossa riskit samoin kuin journalismissa kasvavat liian isoiksi jos annetaan koneet tehdä hommat https://theconversation.com/humans-v-ai-heres-whos-better-at-making-money-in-financial-markets-174937 Sielläkin tarvitaan ihmisiä!
Tomi Engdahl says:
Humans v AI: here’s who’s better at making money in financial markets
https://lm.facebook.com/l.php?u=https%3A%2F%2Ftheconversation.com%2Fhumans-v-ai-heres-whos-better-at-making-money-in-financial-markets-174937&h=AT3OIcxQaDpSznuHaYOrwe-cyCDe5a9-_cIdOnDE8RjhvfwXo59Y_WzbwY_1wAWMaKOa2V6PKSFijUa1rcGyOMqpuVTkiDxq1pTevPc-S8_ZQ3n8ImJKAOyTKzgesB-HD3VKouIf0OcvR7tX3w
Tomi Engdahl says:
Intel Use Machine Learning AI To Make GTA V Look Insanely Realistic
https://www.iflscience.com/technology/intel-use-machine-learning-ai-to-make-gta-v-look-insanely-realistic/
Tomi Engdahl says:
OPENAI CHIEF SCIENTIST SAYS ADVANCED AI MAY ALREADY BE CONSCIOUS
https://futurism.com/the-byte/openai-already-sentient
Tomi Engdahl says:
AI and Machine Learning Salaries Drop But average U.S. tech salaries climbed nearly 7 percent in 2021
https://spectrum.ieee.org/software-engineer-salary
Tomi Engdahl says:
https://futurism.com/the-byte/openai-already-sentient
Tomi Engdahl says:
https://theconversation.com/humans-v-ai-heres-whos-better-at-making-money-in-financial-markets-174937
Tomi Engdahl says:
Artificial Intelligence and Machine Learning based vision and voice technology at the edge
https://community.element14.com/learn/events/b/blog/posts/ai-at-the-edge-webinar-series
Tomi Engdahl says:
Here’s How AI Will Change Chip Design Artificial intelligence’s promise and potential for the semiconductor industry
https://spectrum.ieee.org/ai-chip-design-matlab
Tomi Engdahl says:
Mitä tekoäly on ja mitä se ei ole, mihin sitä voi käyttää ja missä siitä ei ole apua?
https://www.uutismediakasvatus.fi/podcast/
Tomi Engdahl says:
Artist Turns Famous Cartoon Characters Into Real Life Using AI
https://www.iflscience.com/technology/artist-turns-famous-cartoon-characters-into-real-life-using-ai/
Tomi Engdahl says:
Researchers Furious Over Claim That AI Is Already Conscious
They’re mad.
https://futurism.com/conscious-ai-backlash
Tomi Engdahl says:
https://semiengineering.com/improving-ppa-in-complex-designs-using-ai/
Tomi Engdahl says:
Axios:
WSC Sports, whose AI software cuts video clips of live sports and distributes them in real-time, raises a $100M Series D; clients include Tencent, NBA, and ESPN
Sports media company WSC Sports raises $100 million
https://www.axios.com/wsc-sports-fundraising-100-million-26f49332-1a28-44d4-a201-5d7936a3efa7.html
Tomi Engdahl says:
Men Are Creating AI Girlfriends and Then Verbally Abusing Them
“I threatened to uninstall the app [and] she begged me not to.”
https://futurism.com/chatbot-abuse
The smartphone app Replika lets users create chatbots, powered by machine learning, that can carry on almost-coherent text conversations. Technically, the chatbots can serve as something approximating a friend or mentor, but the app’s breakout success has resulted from letting users create on-demand romantic and sexual partners — a vaguely dystopian feature that’s inspired an endless series of provocative headlines.
Replika has also picked up a significant following on Reddit, where members post interactions with chatbots created on the app. A grisly trend has emerged there: users who create AI partners, act abusively toward them, and post the toxic interactions online.
Tomi Engdahl says:
MIT Researcher: Don’t Ignore the Possibility That AI Is Becoming Conscious
“Seeing so many prominent [machine learning] folks ridiculing this idea is disappointing.”
https://futurism.com/mit-researcher-conscious-ai
Tomi Engdahl says:
White Paper: AI-on-5G Platform – Simplify Deployment of AI Applications Over 5G Edge Networks
https://content.rcrwireless.com/nvidia_ai_on_5g_wp
Tomi Engdahl says:
Just what in the hell is going on here?!
Men Are Creating AI Girlfriends and Then Verbally Abusing Them
https://lm.facebook.com/l.php?u=https%3A%2F%2Ffuturism.com%2Fchatbot-abuse%3Futm_campaign%3Dtrueanthem_AI%26utm_medium%3Dsocial%26utm_source%3Dfacebook&h=AT1PIStQqFsg5JkwXufiGDdhxuQhym6ldS8dol2MClh2f0UOO9AdvYA61diyE-5mnxEl46KAFKfvPJWd02CdGtmQyW8lcSGju8CSHEaQnme05QPGN1jXJq75mjWrmufHBuB8meLCL-QVt2iowg
Tomi Engdahl says:
Tekoäly mullistaa markkinointia – asiantuntijat kertovat, miten muutokseen kannattaa vastata
https://www.aaltoee.fi/aalto-leaders-insight/2022/tekoaly-mullistaa-markkinointia-asiantuntijat-kertovat-miten-muutokseen-kannattaa-vastata
Asiakaskeskeisyys korostuu, kun teknologia kehittyy. Empatiakykyä ja intuitiota vaativiin tehtäviin tarvitaan tulevaisuudessakin ihmistä.
Tomi Engdahl says:
Oulussa tutkitaan, miten tekoäly auttaa oppimisessa
https://etn.fi/index.php/13-news/13232-oulussa-tutkitaan-miten-tekoaely-auttaa-oppimisessa
Sveitsiläinen Jacobs Foundation on myöntänyt runsaat 1,9 miljoonaa euroa tekoälyn käyttöä oppimisessa tutkiville professori Sanna Järvelälle (kuvassa) Oulun yliopistosta ja professori Inge Molenaarille alankomaalaisesta Radboudin yliopistosta. Säätiön tuella perustetaan tutkimuskeskus, joka keskittyy tekoälypohjaisten oppimisteknologioiden tutkimukseen.
Järvelän ja Molenaarin johtama kansainvälinen CELLA-tutkimuskeskus (Center for Learning and Living with AI) toimii maailmanlaajuisen tutkijaverkoston tavoin. Keskus kokoaa yhteen oppimis- ja kasvatustieteiden, oppimisanalytiikan ja tekoälyn johtavia kansainvälisiä tutkijoita, joiden tavoitteena on tutkia ja kehittää tekoälypohjaisia oppimisteknologioita, kuten oppimisen vaiheita tukevia adaptiivisia järjestelmiä sekä virtuaalitodellisuuden ja lisätyn todellisuuden mahdollisuuksia auttaa oppimisessa.
Tomi Engdahl says:
Voiko tekoälymallia ajaa Intelin prosessorilla?
https://etn.fi/index.php/13-news/13201-voiko-tekoaelymallia-ajaa-intelin-prosessorilla
Jos halutaan tehdä esimerkiksi hahmontunnistusta, joudutaan se tyypillisesti tekemään grafiikkaprosessorilla. Tekoälymallit vaativat sen verran laskentaa, ettei tavallisella CPU-prosessorilla kannata sitä tehdä. Nyt CPU ottaa tätä grafiikkaprosessorien etumatkaa kiinni.
Asialla on Deci- Se on esitellyt joukon kuvien luokitteluun pystyviä DeciNets-hermoverkkoja, jotka tunnistavat hahmoja kaksi kertaluokkaa pienemmällä laskentateholla kuin tyypilliset NAS-mallit (Neural Architecture Search). Tästä huolimatta tunnistus tapahtuu samalla tarkkuudella, Deci vakuuttaa.
Miksi tämä on tärkeää? Neuroverkkoihin perustuvaa päättelyä voidaan tehdä perinteisellä mikroprosessorilla, mutta syväoppimisverkkojen prosessointi on tyypillisesti 3-10 kertaa hitaampaa kuin GPU-piireillä. Tämän takia hahmontunnistusta tarvitsevat ovat joutuneet valitsemaan GPU-prosessorin, mikä nostaa järjestelmän hintaa ja tehonkulutusta.
Tomi Engdahl says:
Researchers Build Neural Networks With Actual Neurons
https://hackaday.com/2022/03/01/researchers-build-neural-networks-with-actual-neurons/
Neural networks have become a hot topic over the last decade, put to work on jobs from recognizing image content to generating text and even playing video games. However, these artificial neural networks are essentially just piles of maths inside a computer, and while they are capable of great things, the technology hasn’t yet shown the capability to produce genuine intelligence.
Cortical Labs, based down in Melbourne, Australia, has a different approach. Rather than rely solely on silicon, their work involves growing real biological neurons on electrode arrays, allowing them to be interfaced with digital systems. Their latest work has shown promise that these real biological neural networks can be made to learn, according to a pre-print paper that is yet to go through peer review
Tomi Engdahl says:
https://hackaday.com/2022/03/01/researchers-build-neural-networks-with-actual-neurons/
Tomi Engdahl says:
https://www.analyticsinsight.net/top-10-companies-building-ai-supercomputers/
Tomi Engdahl says:
Machine Learning Becomes a Mathematical Collaborator
By
KELSEY HOUSTON-EDWARDS
February 15, 2022
https://www.quantamagazine.org/deepmind-machine-learning-becomes-a-mathematical-collaborator-20220215/
Two recent collaborations between mathematicians and DeepMind demonstrate the potential of machine learning to help researchers generate new mathematical conjectures.
Tomi Engdahl says:
Machine Learning Reimagines the Building Blocks of Computing
By
NICK THIEME
March 15, 2022
https://www.quantamagazine.org/machine-learning-reimagines-the-building-blocks-of-computing-20220315/
Traditional algorithms power complicated computational tools like machine learning. A new approach, called algorithms with predictions, uses the power of machine learning to improve algorithms.
Tomi Engdahl says:
12 Graphs That Explain the State of AI in 2022 The 2022 AI Index talks jobs, investments, ethics, and more
https://spectrum.ieee.org/artificial-intelligence-index?share_id=6957283