I hope flux will include a 3D generation model. right now the open-weights version of 3D is failing behind closed source by a big margin. Hopefully the improved spatial ability helps with robotics too
cool! it's way faster on desktop. I also recompiled to include 3MF support. However on mobile phones compile is still slow even if I set fa to be lower.
While the article emphasis on chaos and short time with China's doctor, they are very accessible, 2 USD you visit a fully trained doctor at top hospital, have your CT scan done the same day with 50 USD even if you pay out of packet.
As for AI, my personal experience is ChatGPT and Gemini is more effective then DeepSeek for healthcare issues. I do hope DeepSeek or Doubao can catch up.
Having worked at both FAANG companies and startups, I can offer a perspective on AI's coding impact in different environments.
At startups, engineers work with new tech stacks, start projects from scratch, and need to ship something quickly. LLMs can wrtie way more code. I've seen ML engineers build React frontends without any previous frontend experience, flutter developers write 100-line SQL queries for data analysis, with LLM 10x productivity for this type of work.
At FAANG companies, codebases contain years of business logic, edge cases, and 'not-bugs-but-features.' Engineers know their tech stacks well, and legacy constraints make LLMs less effective, and can generate wrong code that needs to be fixed
latest llama 3.1 is in a different repo, https://github.com/meta-llama/llama-models/blob/main/models/... , but yes, the code is shared.
It astonishing that in software 2.0 era, powerful applications like llama has only hundreds of lines of code, and most work hidden in training data.
Source code alone is no longer that informative as Software 1.0
Can you elaborate a bit more why render is good? we are on heroku and I have evaluated alternatives every 6 months since heroku/github outage 2 years ago [1]. But I don't see how render is better. 2 years ago render postgres did not have PITR. now they have build it, but Render's postgres offering is even more expensive than heroku, and queries run a bit slower on similar spec machines based on my test. I also don't like render charges per seat in addition to infra cost.
Aside from the content itself, the "Listen to Article" button uses a robotic, outdated TTS voice.
Shouldn't a company like Google use their latest technologies in public-facing content, particularly when discussing AI progress?
I'm genuinely curious about the decision-making process behind this choice.
For my particular cases there are features like shared-mailbox and distribution list that requires additional setups. I don't see a clear advantage to move over a critical provider so I kept things the same. If from dayone I have a choice, I would go with all-in-one.
For example, when sharing a google doc in Gmail, the experience is more feature rich. And if an organization is already paying for gmail, it's hard to stop people from using gdoc and gsheet. In real work, I can't just reply a gdoc share with "use nino or I refuse to read".