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A lot of people talk about AI's impact on jobs. Oracle just put some numbers behind that discussion, cutting 21,000 roles while accelerating its AI push. The transition from AI experimentation to AI implementation is well underway. https://t.co/45VKOcl5RI
https://t.co/dHeVhIcLe5
https://t.co/6eqLRsyvV3 @itsjessyin project!
https://t.co/6eqLRsyvV3 @itsjessyin project!
ever since i was a small boy i knew i wanted to computer https://t.co/u0llIGUzx1
ever since i was a little girl i knew i wanted to computer https://t.co/iOHK59SO2A
ever since i was a small boy i knew i wanted to computer https://t.co/u0llIGUzx1
@michellechen this inspires me. I knew I'd like to work with computeRS, too. https://t.co/PWaKkgxeAa
@michellechen this inspires me. I knew I'd like to work with computeRS, too. https://t.co/PWaKkgxeAa
@jxnlco https://t.co/NuCBHUypTf
@jxnlco https://t.co/NuCBHUypTf
UV curing resin arrived and made life much easier! The graveyard is growing :) https://t.co/JmCiWVlmp3
absurd that LLM benchmarking papers from THIS YEAR are evaluating SUCH OLD MODELS! https://t.co/WQNPBA6dvz
Hermes learned my entire repo in minutes. I’m not exaggerating. I pointed the new /learn skill at my codebase… and watched it turn the repo into a reusable skill. Files. Patterns. Architecture. Commands. Workflows. It didn’t just “read” the repo. It created a playbook for how to work with it again later. This blew my mind. Memory remembers facts. Skills remember how to do the work. That’s the difference. https://t.co/TmBfeZGndP
Your agent can now teach itself from your docs. Hermes /learn turns source material into reusable skills. Feed it: • A codebase • API docs • PDFs/manuals • Configs • Pasted notes • A workflow you just walked through Hermes gathers the context, writes the SKILL.md, and saves i
"I do not believe that AI is likely to cure cancer anytime soon"—@2plus2makes5 https://t.co/7beFUjPfEM In fact, AI has already enabled: —a non-invasive blood test to assay the tumor microenvironment (optimizing the use of immunotherapy, never previously available) — discovery of a 14-protein blood test to prevent lung cancer — guided the selection of neoantigens for personalized vaccines, such as for cure of pancreatic cancer in refractory cases
"I do not believe that AI is likely to cure cancer anytime soon"—@2plus2makes5 https://t.co/7beFUjPfEM In fact, AI has already enabled: —a non-invasive blood test to assay the tumor microenvironment (optimizing the use of immunotherapy, never previously available) — discovery of a 14-protein blood test to prevent lung cancer — guided the selection of neoantigens for personalized vaccines, such as for cure of pancreatic cancer in refractory cases
https://t.co/88RpwILo1P
https://t.co/88RpwILo1P
Two months ago I was fired by Google for creating the Google Workspace CLI. It went viral, hit #1 on Hacker News, gained thousands of GitHub stars and many thousands of actual users in just a couple days. It was an incredible, confusing journey, from directors and leaders asking what they could learn from the tool to getting grilled by legal about why the Google logo and brand colors are on the Google Workspace GitHub code repositories. I think the cause was that Workspace and certain leaders (and projects) were afraid of being disrupted. But the fear wasn't specific to my CLI, it was a broader fear in what agents meant for Workspace. Either way, the irony of my termination was the announcement at Google Cloud Next two days before I was fired that an official Workspace CLI was coming. I want this out there because it is easier for me to explain my story and it is an experience I want to fully own. It's also part of my healing. Nearly 7 years at Google was an incredible opportunity for me and I was fortunate to have wonderful teammates and a manager that fully supported me through these last few months. Thank you.
@OpenAIDevs Imagine a Codex LAN party https://t.co/w9UkQyAsLD
@OpenAIDevs Imagine a Codex LAN party https://t.co/w9UkQyAsLD
Court poster présenté @Institut_Dataia sur les métriques et définitions de la #fairness en #MachineLearning | Revue de littérature des métriques de l'#équité en #IA. 👉https://t.co/jMTdsHdCp8 https://t.co/YVjlzaM8o8
@jxnlco https://t.co/Sdp2FsxF0z
docs: https://t.co/rfQOK0muLR
Seven great design tools with examples from @scuethics https://t.co/5apFa9aMhb
Thoughts? Honestly, it's catching up to Twitter in terms of usefulness to me https://t.co/1KNgrgaE5H
We’re open-sourcing Unlimited OCR — built to read long documents in one pass. With 3B total parameters and only 500M activated, Unlimited OCR sets new end-to-end SOTA results on OmniDocBench v1.5 and v1.6. The key innovation is Reference Sliding Window Attention (R-SWA), inspired by how humans transcribe books: keeping the source, recent context, and next words in focus, while softly forgetting what’s no longer needed. With constant KV Cache size and lower attention cost, Unlimited OCR can transcribe 40+ pages in a single forward pass — without losing context or slowing down. Explore the model👇: --GitHub: https://t.co/5ZJBsEldKd --Hugging Face: https://t.co/4FKFr9EfOu
https://t.co/I1x8xQ3g5T
OMG! Fugu Ultra is ridiculously good at these 3D renders. https://t.co/Noi2CCydEG
https://t.co/3zfJqyJuE2
https://t.co/1b4UZDTMFt
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https://t.co/bNlTKl7PN5
