life goes on by oliver tree. 🕊️

1997: the original agentic experience

I have to say this again. Here is what actually happened. Apple did pause the Vision Air project last year, but not because it gave up on headsets. Internally, Apple concluded that Vision Air was still not light or thin enough. So the company chose a more aggressive path instead. That new project is roughly similar in direction to Meta’s Phoenix, a much lighter and thinner headset. It is being developed by a separate, newer team inside Apple. Apple will probably run another internal review toward the end of this year, comparing Vision Air with this newer, more aggressive direction, before making a final decision on which product to move forward with.

I feel seen vegoutmag.com/living/gen-psy…

NEW POST When I need to feed an LLM a lot of context, I can write it myself, or I can get an LLM to interview me for it. martinfowler.com/bliki/Inter…

We're aware of users experiencing delays connecting to the platform. We are investigating and hope to have this resolved soon! We appreciate your patience. discordstatus.com/incidents/…

After online backlash, Nike took down the sign that read “Runners Welcome. Walkers Tolerated.” on Newbury Street that was put up ahead of the Boston Marathon. runnersworld.com/news/a71052… 📸: Screenshot via @irondoctorhaz

Today we're introducing TRIBE v2 (Trimodal Brain Encoder), a foundation model trained to predict how the human brain responds to almost any sight or sound. Building on our Algonauts 2025 award-winning architecture, TRIBE v2 draws on 500 hours of fMRI recordings from 700 people to create a digital twin of neural activity and enable zero-shot predictions for new subjects, languages, and tasks. Try the demo and learn more here: go.meta.me/tribe2

So proud to see F.03 make history as the first humanoid robot in the White House 🤖 🇺🇸

this is actually insane > be tech guy in australia > adopt cancer riddled rescue dog, months to live > not_going_to_give_you_up.mp4 > pay $3,000 to sequence her tumor DNA > feed it to ChatGPT and AlphaFold > zero background in biology > identify mutated proteins, match them to drug targets > design a custom mRNA cancer vaccine from scratch > genomics professor is “gobsmacked” that some puppy lover did this on his own > need ethics approval to administer it > red tape takes longer than designing the vaccine > 3 months, finally approved > drive 10 hours to get rosie her first injection > tumor halves > coat gets glossy again > dog is alive and happy > professor: “if we can do this for a dog, why aren’t we rolling this out to humans?” one man with a chatbot, and $3,000 just outperformed the entire pharmaceutical discovery pipeline. we are going to cure so many diseases. I dont think people realize how good things are going to get

CNBC's Jon Najarian debuts pre-IPO Immersed's Visor with CEO Renji Bijoy

Full interview: youtu.be/qBlp1tS7UrM?si=f60T…

Red Moon in Austin, TX

Keep your eyes on the sky early tomorrow morning to see the Blood Moon and a total lunar eclipse! 🔴 The Moon will appear dark orange or red as Earth’s shadow blocks most of the Sun’s light from reaching the lunar surface.

Get ready to look up at the sky! A lunar eclipse may catch your eye 🌕 Early tomorrow morning, March 3, a total lunar eclipse will turn the full moon deep red. This occurs when Earth passes directly between the Sun and Moon, casting a shadow across the lunar surface. Learn how and when you can see it: go.nasa.gov/4u9EUla

Pretty crazy when you realize just how flagrant the scaremongering has been about data center water usage:

I think about this a lot.

Trump says US military is launching "massive and ongoing" strikes in Iran. Follow live updates: cnn.it/4r7QnPt

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow. Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes. As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now. It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.