Jev Founder, Diogo Almeida (ex-OpenAI):
"The next era is not the Claude Code or Codex era, they are still part of the assistance era with human in the loop - JEV is what comes next for LLMs
x200 faster, x400 cheaper, 0 hallucination, no human in the loop - that's JEV, this is how LLMs will look like"
in 36-minute tech talk, Jev Founder explained why RLHF isn't a thing anymore and how modern LLMs will be built
this talk is worth more than a Stanford Machine Learning degree
watch today no matter what, then learn how to become a Jev Engineer in the article below
A Google Cloud engineer just showed how to build a complete app with Claude from scratch.
26 minutes, live on stage, doing what most teams take weeks to ship.
Worth more than any $500 vibe-coding course. No team, no setup, just Claude and a goal.
The people learning what Claude can actually do are shipping what everyone else outsources to a team.
Andrew Ng just released a 75-minute Stanford lecture on full AI Engineering.
How to go from chasing perfect prompts to building systems that improve themselves:
00:05 - See why some AI teams move 10X faster
07:12 - Choose an architecture and ship fast
30:12 - Avoid the 97% accuracy trap
48:12 - Run the build → error analysis → retrain loop
57:55 - Build deep-research agents
1:06:30 - Find bottlenecks inside agent pipelines
Most people are still trying to write the perfect prompt.
Andrew Ng is teaching the full stack:
Architecture → Evals → Loops → Agents → Graphs
Prompt engineering is the old workflow.
Building systems that find and fix their own bottlenecks is the new one.
This 75-minute Stanford lecture is worth more than most paid AI engineering courses.
Bookmark and watch it today.
Then read the full agent engineering roadmap below ↓
Maybe it’s just me but over the years i’ve never felt an ounce of difference from any kind of supplement combination I can buy directly on amazon. All just seems like cope
See what Gemini Enterprise means for APAC – LIVE! We'll be livestreaming this session, right here on X. ❤️ Like this post for a reminder when we go live!
Hey @WHOOP I have the issue of late syncing of steps data into Apple health, I’m currently doing steps challenge with my friends, my steps are available just before the midnight, planning to move to my Apple Watch for this https://t.co/ychZnrtjpQ
> be me
> curious how X decides who goes viral and who gets shadowbanned into oblivion
> read the source code. all of it. 400,000 lines
> it's a mess. it's a masterpiece. it's a threat model disguised as a social network
> proceed to get 7M impressions and 7k followers in 9 days
> i have *seen* the algorithm
> here's how to make it your slave
> X is a game
> rules are secret
> stakes are your visibility
> you win by:
> replying to replies (replyguymaxxing)
> baiting profile clicks (profilevisitmax)
> getting bookmarked like you're the Dead Sea Scrolls
> not getting blocked or muted (instant debuff)
> spacing tweets out (diversity filters will kneecap your burst posts)
> every 6 hours, your tweet loses 50% of its power
> decay rate is brutal
> either pop off early or perish
> some actions boost you:
> replies
> retweets
> likes
> bookmarks
> follows after a tweet
> long watch time (10+ sec = algorithmic arousal)
> text read for 2+ seconds = good content juice
> others destroy you:
> blocks
> mutes
> reports
> “see fewer posts like this” clicks
> enjoy being invisible for 3 months
> tweets don't live in a vacuum
> they're judged by:
> real-time engagement
> pagerank-style trust
> reputation graphs
> safety scores
> simclusters (your interest-based tribes)
> content bundles (X’s version of a mixtape)
> simclusters: the secret spice
> you're grouped with users who engage like you
> the algo doesn't care who you follow
> it cares who vibes like you
> proximity = identity
> high cosine similarity with bangers? you *become* a banger
> ranking pipeline:
> 1. light ranker: says maybe
> 2. heavy ranker: massive neural net, runs 1k+ features
> 3. mixer: final DJ, decides who sees what
> you're just a vector in a giant party playlist
> reputation score = Tweepcred
> starts at -128 (yes, minus one twenty-eight)
> verified gets you to 100 instantly
> minimum viable Tweepcred to be seen? 17
> every mute, block, or spam flag? drops it
> don’t tweet in ALL CAPS
> don’t have offensive words in your name or tweet
> don’t link out too much
> yes, there are hidden blacklist files like `adult_tokens.txt` and `offensive_topics.txt`
> yes, they will throttle you into the dirt
> following/follower ratio matters
> follow 5000 people and only 200 follow you back?
> congratulations, you're a bot now
> keep it clean. aim for 1:1.67+
> shadowban?
> not just a myth
> there are actual labels:
> spam
> gore
> toxicity
> low quality
> nsfw
> "mentions person too much"
> each one adds weight to your visibility coffin
> blue check = permission to exist
> legacy verified = bonus points
> no check = enjoy clawing your way out of the void
> diversity filters = anti-spam boss
> prevents 1 account from dominating feeds
> if you're tweeting in bursts, you’re kneecapping yourself
> mix it up. space it out. variety = scrolltime = ads = profit
> virality triggers:
> show up in carousels
> trend modules
> bookmarks
> pinned content
> land here and you're in the algorithm’s VIP lounge
> the algo uses cosine similarity to recommend out-of-network tweets
> turns you and your tweets into embeddings
> measures the angle between you and the bangers
> close enough? you ride their wave
> "become a banger by standing next to one"
> realgraph = who you associate with
> if high-rep people engage with you, your reach improves
> your friends' friends define your fate
> algorithmic nepotism
> want to resurrect an old tweet?
> reply to it
> that reply = defibrillator
> congrats, it's alive again
> wanna go viral?
> curse less
> don’t be cringe
> reply smart
> get bookmarked
> write something that makes them click your profile
> stay relevant, stay recent
> tweet formats that worked before? steal them.
> final boss move?
> join communities
> they push your content harder
> because X loves groupthink
> tl;dr
> the X algo tracks *everything*
> every click, block, mute, and bookmark
> it's not just about what you post
> it's about who interacts with it
> and how much X thinks you matter
> reputation is destiny
> read the code yourself:
> https://t.co/bIdvomui7y
> or don’t. i already did it. you’re welcome.
> now go farm some bookmarks
> but do it with honor
> or at least with style
> algorithm bless
Big news: Amazon is investing $20 to expand AWS data centers across Australia by 2029, the biggest tech investment in aussie history.
Boosting Australia's AI game, renewable energy, and digital skills in one massive move.
AI future looking bright down under 🇦🇺
#AWS#Australia
Google published a 69-page whitepaper on Prompt Engineering and its best practices, a must-read if you are using LLMs in production:
> zero-shot, one-shot, few-shot
> system prompting
> chain-of-thought (CoT)
> ReAct
> code prompting
> best practices
This is Thomas Seyfried.
He’s a professor of biology, who’s studied cancer for 30+ years.
His message? Cancer isn’t bad genes or bad luck—it’s damaged mitochondria.
This flips everything you’ve been told about how to treat & prevent cancer: 🧵