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Today's Topics:
1. NVIDIA Launches Open-Source Ecosystem to Revolutionize
Robotics with Newton Physics Engine and Cosmos Models (Antony Barry)
2. AI has had zero effect on jobs so far, says Yale study
(Stephen Loosley)
3. Interesting implications for peer review (Antony Barry)
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Message: 1
Date: Thu, 2 Oct 2025 18:05:41 +1000
From: Antony Barry <[email protected]>
To: Link list <[email protected]>
Subject: [LINK] NVIDIA Launches Open-Source Ecosystem to Revolutionize
Robotics with Newton Physics Engine and Cosmos Models
Message-ID: <[email protected]>
Content-Type: text/plain; charset=utf-8
Summary of the current webpage:
NVIDIA has launched a major open-source robotics ecosystem, featuring the
Newton Physics Engine, Isaac GR00T reasoning model, and Cosmos world foundation
models?all designed to accelerate robotics research and development.
Newton Physics Engine is now managed by the Linux Foundation and offers
realistic simulation for humanoid robots, enabling safer transfer of skills
from simulation to real-world tasks. It is currently in beta, with resources
available on GitHub.
Broad support for Newton includes universities like ETH Zurich, Peking
University, TUM, and major industry players, with the ecosystem governed openly
and vendor-neutrally by the Linux Foundation for long-term sustainability.
Newton aims to democratize robotics research, reduce development costs, and
foster collaborative innovation.
Cosmos Reason model and Cosmos WFMs have together been downloaded over 4
million times, reflecting strong adoption among developers.
Groot v1.6 improves robot coordination and mobility (arms, joints, movement),
advancing humanoid manipulation skills.
The new Blackwell GPU architecture enables real-time reasoning, path planning,
and AI inference for robots, expanding robotics into logistics, healthcare, and
autonomous applications.
NVIDIA and its partners underscore the goal of moving robotics from research
labs into everyday life?through open models, scalable infrastructure, and
robust simulation tools.
In essence: NVIDIA?s initiative seeks to unify the robotics community and make
advanced physical AI and robotics tools accessible to researchers and industry,
driving faster breakthroughs and wider adoption in real-world settings.brief
<https://www.brief.news/ai/2025/09/29/nvidia-unveils-robotics-platform?categories=Tech&categories=AI&categories=Electric+Vehicles&categories=AI+Research&categories=Gadgets&date=2025-10-01&utm_source=daily-brief&utm_medium=email&source=%2Femail&uid=cm2x5k2i4000he6nukx44a2ye&eid=KZpoUyfe7n>
https://www.brief.news/ai/2025/09/29/nvidia-unveils-robotics-platform?categories=Tech&categories=AI&categories=Electric+Vehicles&categories=AI+Research&categories=Gadgets&date=2025-10-01&utm_source=daily-brief&utm_medium=email&source=%2Femail&uid=cm2x5k2i4000he6nukx44a2ye&eid=KZpoUyfe7n
Summery by Comet (Perplexity AI)
Antony Barry
[email protected]
------------------------------
Message: 2
Date: Thu, 02 Oct 2025 17:53:20 +0930
From: Stephen Loosley <[email protected]>
To: "link" <[email protected]>
Subject: [LINK] AI has had zero effect on jobs so far, says Yale study
Message-ID: <[email protected]>
Content-Type: text/plain; charset="UTF-8"
AI has had zero effect on jobs so far, says Yale study
Other studies are finding the same thing
By Thomas Claburn Wed 1 Oct 2025 // 18:12 UTC
https://www.theregister.com/2025/10/01/ai_isnt_taking_people_jobs/
Yale researchers say that despite the anxiety about AI taking people's jobs,
there's very little evidence of it actually happening.
Economists with Yale's Budget Lab, a non-partisan policy research group, took a
look at how US employment has changed since the November 2022 debut of ChatGPT
and the sequent release of other generative AI models.
They saw nothing to be alarmed about.
"Overall, our metrics indicate that the broader labor market has not
experienced a discernible disruption since ChatGPT?s release 33 months ago,
undercutting fears that AI automation is currently eroding the demand for
cognitive labor across the economy," said Martha Gimbel, Molly Kinder, Joshua
Kendall, and Maddie Lee in a report summary.
The leaders of AI companies have been stoking those fears ? an effective way to
get meetings with lawmakers. In May, Anthropic CEO Dario Amodei expressed
concern that within five years, AI could cut the number of entry-level white
collar jobs in half. OpenAI CEO Sam Altman has made similar pronouncements.
And major companies conducting layoffs like IBM and Salesforce have held
themselves up as examples of that narrative, though their employee culls may be
more focused on outsourcing than automation. Smaller companies like Fiverr have
also cited AI amid layoffs.
AI cheerleader Microsoft recently added fuel to the fire with a report on jobs
most likely to be affected by AI, only to later distance itself from the blaze
by noting, "our study does not draw any conclusions about jobs being
eliminated."
* Microsoft moves to the uncanny valley with creepy Copilot avatars that stare
at you and say your name
* Nadella hands Microsoft money machine off to new commercial CEO so he can
visioneer the future
* JetBrains wants to train AI models on your code snippets
* Google bolts AI into Drive to catch ransomware, but crooks not shaking yet
In Microsoft's own case, the culls appear to be a way to reduce expenses and
mollify investors following its massive capital expenditures on data centers
that fuel its AI ambitions.
The Yale researchers' nothingburger result has precedent. In 2023, a study by
the United Nations International Labour Organization (ILO) concluded that
generative AI would probably not replace most workers.
A study of Danish workers published in April determined that generative AI had
no material impact on wages or jobs. Another such study published in February
found "overall employment effects are modest, as reduced demand in exposed
occupations is offset by productivity-driven increases in labor demand at
AI-adopting firms."
There is some contradictory data. A recent Stanford Digital Economy Lab study
claims that recent college graduates in occupations most exposed to AI have
seen a 13 percent relative decline in employment compared to occupations more
insulated from AI.
But the consensus appears to be that generative AI has not had a meaningful
impact on the labor market so far. Enterprise skepticism of the technology may
be one reason for that.
12 comments
--
------------------------------
Message: 3
Date: Thu, 2 Oct 2025 18:27:08 +1000
From: Antony Barry <[email protected]>
To: Link list <[email protected]>
Subject: [LINK] Interesting implications for peer review
Message-ID: <[email protected]>
Content-Type: text/plain; charset=us-ascii
Summary of paper at the URL below, done by Comet (Perplexity AI)
Tony
Summary: Real AI Agents and Real Work
The Threshold Moment
Professor Ethan Mollick argues that AI has quietly crossed a crucial threshold
- it can now perform real, economically relevant work. This conclusion is based
on OpenAI's new test where experts with 14+ years of experience designed
realistic 4-7 hour tasks, and AI systems came remarkably close to matching
human expert performance.oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
Key Findings
Performance Gap Narrowing: While human experts still won, the margins were
narrow and varied dramatically by industry. The main reasons AI lost weren't
hallucinations or errors, but formatting issues and instruction-following -
areas showing rapid improvement.oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
Tasks vs. Jobs: Mollick emphasizes that while AI can now handle individual
tasks well, it's not replacing entire jobs yet. Jobs consist of many
interconnected tasks, and AI's "jagged" abilities mean it can excel at some
tasks while failing at others requiring complex human
interaction.oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
Real-World Example: Academic Research Replication
Mollick demonstrates AI's capability with a striking example: he gave Claude
Sonnet 4.5 a sophisticated economics paper and its replication data, asking it
to reproduce the findings. Without further instruction, the AI:
Read and understood the paper
Sorted through archive files
Converted statistical code from STATA to Python
Methodically reproduced all findings successfully
This task would normally take human researchers many hours and represents a
potential solution to academia's "replication crisis".oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
The Agent Revolution
Why Agents Work Now: Contrary to expectations, even small improvements in AI
accuracy lead to huge increases in task completion ability. Modern "thinking"
models are self-correcting, meaning they don't get derailed by single errors in
long task chains.oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
Exponential Progress: Data from METR shows consistent exponential gains in AI's
ability to complete long tasks autonomously, from GPT-3 to GPT-5 over five
years.oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
The Two Futures
Mollick warns of two possible paths:
The Nightmare Scenario: Thoughtlessly using AI to do more of what we already
do. He demonstrates this by creating 17 different PowerPoint presentations from
a single memo - highlighting the risk of drowning in AI-generated
content.oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
The Thoughtful Approach: Using human judgment to decide what's worth doing, not
just what can be done. The recommended workflow: delegate to AI first, review
and correct if needed, but do the work yourself if AI can't handle it. This
approach could make work 40% faster and 60% cheaper while maintaining human
control.oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
The Critical Choice
The difference between a productive future and a counterproductive one isn't in
the AI technology itself, but in how we choose to use it. By focusing on making
ourselves more capable rather than just more productive, we can harness AI
agents' power while avoiding the trap of infinite, unnecessary content
generation.oneusefulthing
<https://www.oneusefulthing.org/p/real-ai-agents-and-real-work>
Mollick concludes that AI agents are here now, capable of valuable work, but
their impact depends entirely on our wisdom in deploying them.
https://www.oneusefulthing.org/p/real-ai-agents-and-real-work
Antony Barry
[email protected]
------------------------------
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