Chamath’s first SPAC could be a homerun—Groq? The 3rd and 4th are where retail investors usually get burned. Probably entangled with his data center investment as well.
XAI should:
Make Grok image free and blazing fast, which will burn a lot of cash fast
Watch India and the rest of the world flood in
DAUs and engagement spike
Rewrite the growth narrative
Raise at a premium
XAI should:
Make Grok image free and blazing fast, which will burn a lot of cash fast
Watch India and the rest of the world flood in
DAUs and engagement spike
Rewrite the growth narrative
Raise at a premium
Zuck’s AI strategy isn’t about building personal superintelligence. It’s about two things:
1.Compressing AI margins—possibly over 50%—to benefit Meta’s ads business, and
2.Undermining the next wave of consumer apps targeting billions of users.
Groq might be nearing an agreement with xAI or Tesla to handle a pilot inference workload. That could explain why Chamath’s been hyping them up so much lately.
next move of XAI after grok3 release is earning 1b revenue from tesla, space x, and US gov (probably via PLTR to obfuscate conflict of interest), to keep raising money at higher valuation
Fsd rebranded to “supervised” means current hardware is not “fsd-ready”. Newer models may increase in size and therefore need more powerful inference chip. People are expecting to use their car for Robotaxi, but seems unlikely given its hardware will simply cost more.
next move of XAI after grok3 release is earning 1b revenue from tesla, space x, and US gov (probably via PLTR to obfuscate conflict of interest), to keep raising money at higher valuation
One question for @elonmusk: are you going to update the X algorithm on GitHub again? It's obvious that it has little to do with what it was two years ago.
1/8 Let's try something new !
For several years now, I've been teaching a master-level course in software reverse engineering and protection at the @hes_so.
this christmas, i am humbly asking for your help to support dr. hankinson's research.
if not with $, i would be just as grateful for a repost or a like on this thread.
100% of your donation goes directly to funding the research efforts of Hankinson Lab: https://t.co/z8DcECGXGS
- Review PRs assigned to me and create draft comments
- Create expense reports for my home biz and categorize them. Which item qualifies for tax credit?
The next obvious move for LLM apps is creating memories based on your emails and chat apps, index, perform background tasks, and create a bunch of draft actions for you to review/ack. Some examples:
- Where're my insurance policies, how much do they increase yoy --> get me some quotes
- Which trial subscriptions are about to expire -> one click to cancel or cancel by default
- Read new Github issues sent to by inbox, triage and produce draft PRs