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Category: robotics/AI – Page 1,308

New AI tool can generate faster, accurate and sharper cosmic images

The team was able to produce blur-free, high-resolution images of the universe by incorporating this AI algorithm.

Before reaching ground-based telescopes, cosmic light interacts with the Earth’s atmosphere. That’s why, the majority of advanced ground-based telescopes are located at high altitudes on Earth, where the atmosphere is thinner. The Earth’s changing atmosphere often obscures the view of the universe.

The atmosphere obstructs certain wavelengths as well as distorts the light coming from great distances. This interference may interfere with the accurate construction of space images, which is critical for unraveling the mysteries of the universe. The produced blurry images may obscure the shapes of astronomical objects and cause measurement errors.

MIT’s Codon compiler allows Python to ‘speak’ natively with computers

Researchers at MIT created Codon, which dramatically increases the speed of Python code by allowing users to run it as effectively as C or C++.

Python is one of the most popular computer languages, but it has a severe Achilles heel; it can be cumbersome compared to lower-level languages like C or C++. To rectify this, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) set out to change this through the development of Codon. This Python-based compiler allows users to write Python code that runs as efficiently as a program in C or C++.

Arsenii Palivoda/iStock.

In order to identify the type at runtime, Saman Amarasinghe, an MIT professor and lead investigator for the CSAIL who is also a co-author of the Codon paper, notes that “if you have a dynamic language [like Python], every time you have some data, you need to keep a lot of additional metadata around it.”

AI chip race: Google says its Tensor chips compute faster than Nvidia’s A100

It also says that it has a healthy pipeline for chips in the future.

Search engine giant Google has claimed that the supercomputers it uses to develop its artificial intelligence (AI) models are faster and more energy efficient than Nvidia Corporation’s. While processing power for most companies delving into the AI space comes from Nvidia’s chips, Google uses a custom chip called Tensor Processing Unit (TPU).

Google announced its Tensor chips during the peak of the COVID-19 pandemic when businesses from electronics to automotive faced the pinch of chip shortage.

AI-designed chips to further AI development

Interesting Engineering reported in 2021 that Google used AI to design its TPUs. Google claimed that the design process was completed in just six hours using AI compared to the months humans spend designing chips.

For most things associated with AI these days, product iterations occur rapidly, and the TPU is currently in its fourth generation. As Microsoft stitched together chips to power OpenAI’s research requirement, Google also put together 4,000 TPUs to make its supercomputer.

Continue reading “AI chip race: Google says its Tensor chips compute faster than Nvidia’s A100” | >

Mind control: 3D-patterned sensors allow robots to be controlled by thought

This novel technology looks like a sci-fi device. But it’s real.

It seems like something from a science fiction movie: a specialized, electronic headband and using your mind to control a robot.

Oonal/iStock.

A new study published in the journal ACS Applied Nano Materials took a step toward making this a reality. The team produced “dry” sensors that can record the brain’s electrical activity despite the hair and the bumps and curves of the head by constructing a specific, 3D-patterned structure that does not rely on sticky conductive gels.

New Stanford report highlights the potential, costs, and risks of AI

AI-related jobs are on the rise but funding has taken a dip.

The technology world goes through waves of terminologies. Last year, was much about building the metaverse until it turned to artificial intelligence (AI) which has occupied the top news spots almost everywhere. To know whether this wave will last or wither off, one needs to look at some trusted sources in the domain, such as the one released by Stanford University.

For years now, the Institute for Human-Centered Artificial Intelligence at Stanford has been releasing its AI Index on an annual basis.

Black_Kira/iStock.

With AI occupying center stage for the past few months, the AI Index is a valuable resource to see what the future holds.

Joe Biden warns of AI dangers, urges tech companies to make safe products

Social media has already illustrated the harm that powerful technologies can do without the right safeguards, said the President.

U.S. President Joe Biden warned of the dangers of using artificial intelligence (AI) while putting the onus on making safe products on technology companies.

The White House/ Wikimedia Commons.

Although Musk was one of the co-founders of OpenAI. Recently the Tesla CEO co-signed a letter asking for a six-month moratorium on AI research and stopping companies from releasing products more powerful than GPT-4.

Stephen Wolfram on AI’s rapid progress & the “Post-Knowledge Work Era” | E1711

(0:00) Nick kicks off the show.
(1:24) Under the hood of ChatGPT
(7:53) What is a neural net?
(10:05) Cast.ai — Get a free cloud cost audit with a personal consultation at https://cast.ai/twist.
(11:33) Determining values and weights in a neural net.
(18:28) Vanta — Get $1000 off your SOC 2 at https://vanta.com/twist.
(19:33) Emulating the human brain.
(23:26) Defining computational irreducibility.
(26:14) Emergent behavior and the rules of language.
(31:49) Discovering logic + creating a computational language.
(38:10) Clumio — Start a free backup, or sign up for a demo at https://clumio.com/twist.
(39:38) Wolfram’s ChatGPT plugin.
(43:46) The rapid pace of AI
(58:45) The “Post-Knowledge Work” era.
(1:03:52) The unintended consequences of AI
(1:11:45) Rewarding innovation.
(1:16:12) The possibility of AGI
(1:20:07) Creating a general-purpose robotic system.

Check out Wolfram Research: https://www.wolfram.com/

FOLLOW Stephen: https://twitter.com/stephen_wolfram.
FOLLOW Jason: https://linktr.ee/calacanis.

Thanks to our partners:
(10:05) Cast.ai — Get a free cloud cost audit with a personal consultation at https://cast.ai/twist.
(18:28) Vanta — Get $1000 off your SOC 2 at https://vanta.com/twist.
(38:10) Clumio — Start a free backup, or sign up for a demo at https://clumio.com/twist.

Listen here:
Apple: https://podcasts.apple.com/us/podcast/this-week-in-startups-audio/id315114957
Spotify: https://open.spotify.com/show/6ULQ0ewYf5zmsDgBchlkr9
Overcast: https://overcast.fm/itunes315114957/this-week-in-startups-audio.

How to Survive the AI Revolution

Is artificial intelligence on the path to replacing people and jobs? Not quite. GSB professors argue that instead of viewing #AI as a competitor, we should be embracing it as a collaborator.

“The idea that AI is aimed toward automation is a misconception. There’s so much more opportunity for this technology to augment humans than the very narrow notion of replacing humans.” Professor Fei-Fei Li, co-director of the Stanford Institute for Human-Centered Artificial Intelligence.
Link to

Dozer exits stealth to help any developer build real-time data apps ‘in minutes’

Data has emerged as one of the world’s greatest resources, underpinning everything from video-recommendation engines and digital banking, to the burgeoning AI revolution. But in a world where data has become increasingly distributed across locations, from databases to data warehouses to data lakes and beyond, combining it all into a compatible format for use in real-time scenarios can be a mammoth undertaking.

For context, applications that don’t require instant, real-time data access can simply combine and process data in batches at fixed intervals. This so-called “batch data processing” can be useful for things like processing monthly sales data. But often, a company will need real-time access to data as it’s created, and this might be pivotal for customer support software that relies on current information about each and every sale, for example.

Elsewhere, ride-hail apps also need to process all manner of data points in order to connect a rider with a driver — this isn’t something that can wait a few days. These kinds of scenarios require what is known as “stream data processing,” where data is collected and combined for real-time access, which is far more complex to configure.

AGI Unleashed: Game Theory, Byzantine Generals, and the Heuristic Imperatives

Patreon: https://www.patreon.com/daveshap.
GitHub: https://github.com/daveshap.
Cognitive AI Lab Discord: https://discord.gg/yqaBG5rh4j.

Artificial Sentience Reddit: https://www.reddit.com/r/ArtificialSentience/
Heuristic Imperatives Reddit: https://www.reddit.com/r/HeuristicImperatives/

DISCLAIMER: This video is not medical, financial, or legal advice. This is just my personal story and research findings. Always consult a licensed professional.

I work to better myself and the rest of humanity.

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