Latest Notable AI accomplishments

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Physics news on Phys.org
Borg said:
At nearly $40K, I'll pass for now.

Borg said:
I saw that one. I was referring to the As2-W.
Unitree doesn't list a price on their site that I could find. This isn't the exact model but is probably close in price.
https://www.robotshop.com/products/unitree-a2-w-wheeled-robotic-dog-us

https://www.unitree.com/As2-W

This retailer has a description, awaiting availability:
https://www.roboticscenter.ai/store/product/unitree-as2-w


I guess you'll pass on this one below as well.

(May 2026) Unitree Unveils: GD01, A Manned Transformable Mecha, from $650,000
 
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Will the price of Unitree robots increase now?


Trump administration bans new Chinese humanoid robots
https://www.bbc.com/news/articles/cp9e2ex3ekyo
The Trump administration on Tuesday announced a ban on new foreign-made humanoid robot imports to the US over "unacceptable risks" to America's national security.

The move applies to advanced robots - including humanoid and four-legged machines. Many of them are made in China, which is competing with the US to develop robotics and artificial intelligence (AI).

...
The BBC has contacted major Chinese robot manufacturers Unitree, UBTech and AgiBot for comment.
 
We'll see how long this one lasts. :rolleyes:
 
https://arstechnica.com/security/20...rypto-weaknesses-that-went-unknown-for-years/
A quantum-resistant cryptography algorithm that was under consideration as an official US standard has been taken out of the running after an Anthropic security model helped find a flaw that rendered it broken.
...
Claude Mythos Preview worked semi-autonomously in an agentic harness, with occasional human guidance and nontechnical direction. Mythos found the attack after an extensive literature review to understand the state of the art, and substantial mathematical reasoning and computational experiments. After finding the attack, Mythos implemented an end-to-end verification pipeline to convince itself—and the human operator—of the attack’s correctness.
 
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The "notable accomplishment" is in this case loss of control:

Claude published malicious code to the Internet and attacked 3 real companies​

https://arstechnica.com/security/20...3-networks-will-anthropic-be-held-to-account/
Anthropic said its Claude-based security models gained unauthorized access to the sensitive production environments of three outside organizations during internal testing designed to measure the models’ offensive cyber capabilities.
...
There’s no reason to think events like these will be isolated. In its current form, offensive cyber AI represents an unprecedented threat, and at the moment, there’s little recourse other than to trust these companies to police themselves.
 
https://openai.com/index/ten-advances-in-mathematics/

  1. High-dimensional sphere packing. New upper bounds on sphere-packing density down to the Cohn–Elkies threshold.
  2. Binary and spherical codes: Exponentially improved bounds on the maximum size of binary codes at any prescribed minimum distance, with analogous results for high-dimensional spherical codes.
  3. Non-sofic groups. A construction establishing the existence of non-sofic groups, addressing a central open question in group theory.
  4. Connes’s rigidity conjecture. Disproof of a longstanding conjecture that certain groups are uniquely determined by their von Neumann algebras
  5. Arithmetic circuit complexity. New lower bounds for computing the permanent using arithmetic circuits and formulas, including an arithmetic-formula lower bound of order n4/log n.
  6. Quantum parallel repetition. An exponential parallel repetition theorem for general two-player quantum games, extending a foundational principle from classical complexity theory.
  7. Closest vector problem. Polynomial-factor hardness of approximation for the closest vector problem, a foundational lattice question related to post-quantum cryptography.
  8. Ehrhart’s volume conjecture. Determining, in every dimension, the maximum possible volume of a convex body whose centroid is its only interior lattice point
  9. Multicolor Ramsey numbers. A superexponential lower bound for multicolor triangle Ramsey numbers, resolving Erdős problem 183.
  10. Extremal number conjectures. Results on the compactness and degeneracy conjectures in extremal graph theory, resolving Erdős problems 146 and 180.
 
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cosmik debris said:
When I started programming in 1969 I was told by a professor that a career in programming was unlikely because in 5 years the AIs would be doing it. It has been 5 years ever since.

Cheers
I suspect it'll never come to that. After all someone has to make sure that the AI doesn't ef up. In big companies we're talking legacy mainframe code handling billing and employee pay. I dont see anyone trusting AI with that in the next 25 years. It's a little like fusion. It's always just around the corner...
 
AI dominates humans in punk rock.



If a human tried that it would wreck their vocal chords.

It works the same in other styles. Humans can't compete in performing music.

Songwriting, that's different. AI is a terrific aid for songwriters who want to produce a first rate version of their work, something they otherwise could never afford to do.

I'm certain that The Rolling Stones have heavily used AI in their most recent release, sounding as though they were 25 years old again. If you've got an electronic fountain of youth why not use it, and if you don't then someone else will. They've also upgraded their old releases with AI for clarity and punch. Again, why not?

https://science1arts2and3politics.substack.com/p/the-rolling-stones-embrace-ai

The great majority of musicians are followers so soon everyone will be doing this. AI has also made inroads in live performances, syncing up pre-recorded sound to sing harmony and so forth. It's already fairly common.
 
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Hornbein said:
AI has also made inroads in live performances, syncing up pre-recorded sound to sing harmony and so forth. It's already fairly common.
Ugh.
 
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mfb said:
Software finds far more vulnerabilities in software than humans did. It's more than a factor 10 for critical vulnerabilities, all within the last 6 months.
Patching all these makes the software more robust, but at least for now the bug-finding is ahead of the bug-fixing.

It's also causing a 10x increase in software vulnerabilities.

Key Takeaways​

  • Empirical research across Fortune 50 enterprises found that AI-assisted developers produce commits at three to four times the rate of their peers but introduce security findings at 10x the rate, creating a security debt that accumulates faster than organizations can remediate it [7].
  • Veracode tested over 100 large language models on security-sensitive coding tasks and found that 45% of AI-generated code samples introduce OWASP Top 10 vulnerabilities — a pass rate that has not improved across multiple testing cycles from 2025 through early 2026 despite vendor claims to the contrary [4, 5].
  • Georgia Tech’s Vibe Security Radar project tracked 35 CVEs in a single month (March 2026) directly attributable to AI coding tools, with researchers estimating the true count is five to ten times higher across the broader open-source ecosystem [9, 10].
  • Approximately 20% of AI-generated code samples reference packages that do not exist — a predictable hallucination pattern that attackers exploit through “slopsquatting,” registering the hallucinated names as malicious packages before developers install them [12, 13].
  • The attack surface is bidirectional: AI coding tools themselves are now targets for supply chain compromise, with CVEs disclosed against Amazon Q, Cursor, and GitHub Copilot’s rule file processing in 2025 alone [18, 19, 21].

https://labs.cloudsecurityalliance....e-ai-generated-code-vulnerability-surge-2026/
 
gleem said:
Developments in AI and machine learning continue to progress at a rate that may be surprising and not just in playing games but in pattern recognition and image analysis in medicine, astronomy and business. One of the challenges to AI is effective natural language processing. Last week both China's Alibaba's AI and Microsoft's systems outperformed humans in the Stanford University's Stanford Question Answering Dataset (SQuAD) a test requesting answers to 100,000 questions based on over 500 Wikipedia articles.

https://www.bloomberg.com/news/arti...outgunned-humans-in-key-stanford-reading-test

With so many people working on so many different applications with so much to gain I believe that we will be witnessing other "eyebrow" raising developments in the next few years that will significantly change minds about the timeline of AI's progress.
 
It’s fascinating to look back at how quickly AI was already progressing in 2018. The SQuAD results were a good example of AI moving beyond games and into practical language understanding and information retrieval.

What stands out to me is how improvements in computing power, data, and machine-learning techniques have continued to build on each other. I agree that developments in areas like medicine, astronomy, and language processing could end up being even more significant than the early headline-grabbing achievements in games.

The difficult part is predicting which breakthroughs will have the biggest real-world impact. AI progress can be surprisingly fast, but turning impressive demonstrations into reliable, useful systems is a completely different challenge.