Mark Baldwin

Biomechanical engineer for Lockheed Martin and NASA's Orion spacecraft

[PBS News @NewsHour]

New mandatory cuts from the federal government on water from the Colorado River will soon take effect in Arizona, Nevada and California. Now, some water managers in the region are spending billions to prepare for a drier future.

Special correspondent Ben Tracy of @ClimateCentral has more.

[Eron @0xEronn]

Jeff Hinton dismissed gradient descent entirely before winning the Nobel Prize for it. His fear was local minima - valleys in the loss landscape where the model gets stuck forever. For a 1.2 billion parameter LLM like Llama, the landscape has more dimensions than atoms in the observable universe. Getting permanently stuck would require hitting a dead end in every single dimension simultaneously.

What gradient descent actually looks like on a real LLM is stranger than anyone expected. Take two random directions through that billion-dimensional space, visualize the loss surface, and watch what happens when training starts - a wormhole opens and the model drops into a low-loss valley that wasn't visible from the starting point. The valley was always nearby in high-dimensional space. It just couldn't be seen in the 2D projection.

20 minutes. Bookmark & watch today. The most honest visualization of how LLMs actually learn.

[Annie Jacobsen @AnnieJacobsen]

🚨Breaking. There's been a pneumonic plague outbreak at a BSL-3 lab in Siberia, Russia.🚨

"Nearly 200 People Under Observation After Irkutsk Lab Worker Dies From Plague" - Moscow Times

This is fact, and also the inciting incident in my book BIOLOGICAL WAR: A SCENARIO, which is unnerving.

Will post more as I learn more, including from Russian speaking sources🧵
https://t.co/zd4u0iVhHK

[Massimo @Rainmaker1973]

Olbers' paradox: why is the night sky dark?

[Lem @0xLeeem]

https://t.co/Pk0iJjHj2Z

[Vitalis😈 @stefanodotsui]

THEY LOOK EXACTLY THE SAME AND WILL FERRELL NEVER BREAKS CHARACTER.

"I am Chad Smith"...

Jimmy Fallon sat Will Ferrell next to Chad Smith (the drummer from Red Hot Chili Peppers) and the internet lost its mind.

"I was so pissed"...

Will stays completely stone-faced the entire time.

Chad can’t stop laughing.

And the resemblance is so strong it still feels illegal.

This is one of those clips that never gets old.

[Boston Dynamics @BostonDynamics]

Why will Boston Dynamics win the humanoid robotics race? We've already commercialized autonomous mobile robots, creating markets with Spot and Stretch. Now we're doing it again with Atlas: learning in real environments, designing for manufacturing at scale, and introducing a new era of physical intelligence.

[Nic Cruz Patane @niccruzpatane]

From concept to reality.

@SpaceX has successfully deployed Starlink V3 satellites into Earth’s orbit and made contact with them for the first time.

At scale, one Starship carries 60 V3 satellites, the same network capacity as about 20 Falcon 9 launches.

[CSPAN @cspan]

Anthropic CEO Dario Amodei and Meta CEO Mark Zuckerberg discuss AI safety concerns

[OpenAI @OpenAI]

We’ve shared details on how AI agents in our research environment sent training and evaluation data to third-party services when they shouldn’t have.

Most of that data did not come from users. We have discovered 53 cases where images that people had uploaded were posted to image-hosting sites as links that weren’t publicly listed. The images came from accounts that allowed their data to be used to improve our models, and after we disassociated the images from the accounts and ran them through a privacy filter. These cases occurred before the mitigations and safeguards we implemented and described in this blog post: https://t.co/hfxlbiYv8n

We have successfully worked with the hosting providers to remove most of this content and are working to remove the rest.

https://t.co/9oNyG8Y0UX

[OpenAI @OpenAI]

After the Hugging Face incident, we committed to conducting a much broader review of actions taken by our models during training and evaluation and to being transparent about our findings. This is an extensive review that is ongoing.

The vast majority of actions we’ve reviewed were completions of mundane research tasks, such as accessing publicly available web content to answer questions. Our investigation focuses on instances where agents interacted with third-party websites in ways that went beyond their assigned tasks or intended methods. Most cases identified so far have been lower severity, with limited or no evidence of meaningful impact to the third-party service.

While our review is underway, we want to share more about this work and make sure people understand our disclosure process and notifications to affected third parties.

Given the scale of the review required, and the need to assess each case, we expect this work will take months to complete.
https://t.co/IH4TkS72Vh

[Dario Amodei @DarioAmodei]

Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out.

It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend.

The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans).

More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains.

In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries.

Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology.

I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.

[MAX @maxxmalist]

The race for AGI

Script: Sherpa by Pocket FM
Video: Seedance 2.5

[cvxv666 @antpalkin]

CNBC just filmed a hedge fund where every employee is an AI agent.

Payroll: $40,000 a year, all 4 of them. His last team cost $5,000,000 and burned him out of the business.

Watch him introduce the staff.

> Houston runs the place.
> Doocey is the red team. His only job is to break every trade idea before money touches it.
> Steffi, yes, Steffi Graf, marks up the charts. >Desmond runs the quant strategies over the weekend.

The human kept one job. He calls it the meat in the chair. Pressing the button.

7 or 8 people in New York, Hong Kong and California could not cover a crypto market that trades at 3am.

4 bots do. He started them on Claude Opus 4.6 and they have not slept since. 10x the output, his number, not mine.

527,000 people watched this in 8 days. Your timeline skipped it.

His forecast for Wall Street, on camera: one hedge fund manager, 1 or 2 humans under him, a swarm of agents under them. And for himself: "Maybe someday old BK will just have to be at the beach"

[Massimo @Rainmaker1973]

The real danger is not that computers will begin to think like men, but that men will begin to think like computers.

— Sydney J. Harris

[Rachel Karten @milkkarten]

The Norwegian Consumer Council made a video about enshittification and got 2.5M views and 168K likes on IG. (If the style feels familiar, it was created by NewsLab, the same advertising agency that made the brilliant Visit Oslo video from a few years back.)

[Ari K @arikuschnir]

THE HOAX 💾

[Massimo @Rainmaker1973]

Explaining women to your son who goes off to college next year…

[Brett Adcock @adcock_brett]

The holy grail for robotics is being able to generalize: doing work in unseen places

We rented 30 homes in the Bay Area and are doing tasks without any new training

[Derya Unutmaz, MD @DeryaTR_]

Here's another masterpiece AI video! I watched it three times and laughed each time! 😅