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“Eureka 1” is an innovative underwater drone that can collect rare minerals from the seafloor without causing too much damage to the ecosystem.

Impossible Metals has announced in a press release that “Eureka 1,” its first autonomous underwater vehicle (AUV), has finished its first field test by carefully choosing pebbles to collect in an aquatic environment. This is a big step for the company, which wants to move toward a green economy by finding better ways to mine essential minerals.

This will be important because the demand for these metals will keep going up for the next few decades.


Impossible Metals.

All of this puts a massive strain on mining activities and will lead to a rise in demand for traditional and new ways to get raw materials.

According to press releases, it has now been confirmed that the UK will team up with Japan and Italy to develop a new 6th-generation jet fighter called “Tempest.”

Britain, Italy, and Japan said in a joint statement, as reported by Defense News, that they would be working together to create a new sixth-generation fighter. Before this release, there were rumors of such a project under the so-called Global Combat Air Programme (GCAP), but nothing more was known beyond the fact that the partners wanted to have the fighter ready by 2035.

According to the BBC, it is anticipated that the new “Tempest” fighter, as it has been called, will also be able to carry the latest in advanced weaponry.


BAE Systems.

Work has already started on making a combat plane that is fast, quiet, has cutting-edge sensors, and can even use artificial intelligence to help pilots when they are overwhelmed or under a lot of stress. It might also be able to fire hypersonic missiles and fly without a pilot if needed.

OpenAI released a new chatbot called ChatGPT which is insanely good in human conversation. It also writes code with very high accuracy. What is going to happen to all programming jobs and data scientist jobs now? Let’s see a demo of ChatGPT and discuss a few important concerns associated with this. Towards the end of the video, I will ask a question that will do a rest test on ChatGPT’s ability to replace programmer job, you will be amazing to see how ChatGPT responds to that specific query 😊

Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&…escription for my affordable video courses.

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AlphaCode received an average ranking in the top 54.3% in simulated evaluations in recent coding competitions on the Codeforces competitive coding platform when limited to generation 10 solutions per problem. 66% of those problems, however, were solved using its first submission.

That might not sound all that impressive, particularly when compared to seemingly stronger model performances against humans in complex board games, though the researchers note that succeeding at coding competitions are uniquely difficult. To succeed, AlphaCode had to first understand complex coding problems in natural languages and then “reason” about unforeseen problems rather than simply memorizing code snippets. AlphaCode was able to solve problems it hadn’t seen before, and the researchers claim they found no evidence that their model simply copied core logix from the training data. Combined, the researchers say those factors make AlphaCode’s performance a “big step forward.”

Google’s DeepMind AI division has tackled everything from StarCraft to protein folding. So it’s probably no surprise that its creators have eventually turned to what is undoubtedly a personal interest: computer programming. In Thursday’s edition of Science, the company describes a system it developed that produces code in response to programming typical of those used in human programming contests.

On an average challenge, the AI system could score near the top half of participants. But it had a bit of trouble scaling, being less likely to produce a successful program on problems where more code is typically required. Still, the fact that it works at all without having been given any structural information about algorithms or programming languages is a bit of a surprise.

GPT-3 and Google Sheets


https://sheets.new/
https://beta.openai.com/account/api-keys.

Mentioned in this stream:
https://jalammar.github.io/how-gpt3-works-visualizations-animations/
https://c4-search.apps.allenai.org/?q=%22James+Gosling%22
https://beta.openai.com/codex-javascript-sandbox.

The GPT-3 Leta video series


https://galactica.org/explore/

Roadmap: AI’s next big steps in the world

The Memo: https://lifearchitect.ai/memo/

Inside language models (from GPT to Nova)

Dr Alan D. Thompson is a world expert in artificial intelligence (AI), specialising in the augmentation of human intelligence, and advancing the evolution of ‘integrated AI’. Alan’s applied AI research and visualisations are featured across major international media, including citations in the University of Oxford’s debate on AI Ethics in December 2021.

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Starlink and T-Mobile’s partnership will be revolutionary for cellular service and Smarter AI CEO Chris Piche had some thoughts on how the new partnership will impact 5G capability for the automotive industry.

Chris, who has created services including AT&T TV, BBM Video, Poly Video, and STUN/TURN/ICE shared his thoughts on the effect of 5G on vehicles and telecommunications in an interview with Teslarati.

AI CAMERAS, TESLA, STARLINK & AUTONOMOUS VEHICLES Before founding Smarter AI, the Top 40 under 40 entrepreneur’s company created a technology that BlackBerry licensed to enable voice and video calling. This gave Chris a front-row seat to witness the speed at which technology can transform markets.

Thousands of Ukrainian soldiers and civilians are suffering unimaginable injuries in the country’s war with Russia. Many of the more seriously wounded have lost one or more limbs. Now a company in New York is stepping up to help. For access to live and exclusive video from CNBC subscribe to CNBC PRO: https://cnb.cx/2NGeIvi.

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Using new machine learning techniques, researchers at UC San Francisco (UCSF), in collaboration with a team at IBM Research, have developed a virtual molecular library of thousands of “command sentences” for cells, based on combinations of “words” that guided engineered immune cells to seek out and tirelessly kill cancer cells.

The work, published online Dec. 8, 2022, in Science, represents the first time such sophisticated computational approaches have been applied to a field that until now has progressed largely through ad hoc tinkering and engineering cells with existing—rather than synthesized—molecules.

The advance allows scientists to predict which elements—natural or synthesized—they should include in a cell to give it the precise behaviors required to respond effectively to complex diseases.