nandan

[Charly Wargnier @DataChaz]

🚨 @3BLUE1BROWN DID IT AGAIN

Language compressibility is not just a neat math trick: it is the core engine of modern LLMs.

Grant's latest video boils Shannon's entropy down to a single, powerful idea:

Prediction IS compression.

→ Predict the next word better, use fewer bits to store it
→ Shannon found English is astonishingly compressible (~1 bit per character)
→ This is the exact mechanism GPT models run on
→ Under this framing, intelligence equals compression

FUN FACT: Von Neumann told Shannon to use the term "entropy" because no one really understands it.

Today, it powers the AI revolution.

Deep-dive resources in the 🧵↓

[໊ @oboo_emma_]

mexico genuinely has one of the best stadiums at this world cup, but they’re not getting the hype they deserve. that view is absolutely insane man.🇲🇽

[Deepak Prabhu @ragiiing_bull]

Anant Maam speaking in Konkani.

[Google Research @GoogleResearch]

Today we present a study on how reasoning unlocks parametric knowledge in LLMs. We identify two key driving mechanisms, a computational buffer effect and factual priming, and suggest ways that can help build more reliable models. Learn more: https://t.co/CjIKqyoG4N

[The Scientific Lens @LensScientific]

"What we observe as material bodies and forces are nothing but shapes and variations in the structure of space and time."

– Erwin Schrödinger

[Nate Matherson @NateMatherson]

If your WFH desk setup doesn't cost more than a used Honda Civic, you aren't serious about your pipeline.

My ergonomic chair is built from the salvaged suspension of a 2019 Tesla Model S.

My primary monitor is a converted IMAX screen I bought from a bankrupt theater in Oakland.

When I drag a cell in Google Sheets, I physically have to rotate my entire torso. I burn 400 active calories a day just searching for the Slack icon.

Stop complaining about back pain and optimize your environment.

[Math Lady Hazel 🇦🇷 @mathladyhazel]

The Fibonacci elephant.

[tetsuo @tetsuoai]

"You can't engineer luck."

The cleanest framing of P vs NP I've heard.

MIT 6.006 Introduction to Algorithms.

[Nepali ( Gorkhali ) 𝕏🇳🇵🇵🇸 @EnigmaNepali]

@tanik_tr Can’t beat NEPALI 🇳🇵 TIGER THOUGH 🤣

[nandan @nandan796201]

@KFC_India It reached after 1 hour.

[nandan @nandan796201]

It's been 30 mins and my order has not reached till now. Map shows the rider is still at the store.
I can't even call to the number you shared on app.
@KFC_India

[SHD766 @MohdSha66621889]

TOP 4 RANKING BAT BREAKING DELIVERIES.

WHICH ONE IS BEST ?

[OldMonkOfCricket @OldMonkOfCric]

The day Alastair Cook proved his reflexes are not human🤯🔥

[Hugging Models @HuggingModels]

Gemma 4 12B Coder is here and it's a game changer for local code generation. This GGUF model packs Google's latest gemma-4 architecture into a compact 12B size, perfect for running on consumer hardware. It's optimized for reasoning and thinking, making it ideal for developers who want fast, private coding assistance without the cloud.

[Animal signal @Animalsignal02]

End of Era. Machali (T-16) Queen of Ranthambore, Crocodile Killer.

The legendary tigress who ruled the wild has breathed her last

These final moments of the greatest queen Ranthambore has ever known. A chapter of tiger history closes forever

[Vaibhav Sisinty @VaibhavSisinty]

Google just made AI memory 10x cheaper. And the idea is something a 10-year-old could understand. 🤯

Here's the problem.

Every time you talk to ChatGPT or Claude, the AI remembers every single word of your conversation. That's what makes it smart. But it's also what makes it expensive. The longer you talk, the more it costs to run.

The alternative is to compress everything into one tiny memory. Cheaper, but the AI starts forgetting what you said 5 minutes ago.

Google's fix: what if the AI just saved snapshots of its memory at regular intervals?

Instead of remembering every word or compressing everything into one blob, it saves a checkpoint after every chunk of conversation. When it needs to recall something, it checks all past checkpoints.

Think of it like this. Instead of writing a 100-page book summary in one paragraph, you write a short summary after every 10 pages and keep all of them. When someone asks a question, you check all 10 summaries.

The result: nearly the same recall ability as today's AI. At a fraction of the cost.

And you can tune exactly how many checkpoints to save more checkpoints = better memory, fewer = faster and cheaper.

This is how AI gets cheaper to run without getting dumber.

Paper from Google Research: https://t.co/XQ2OpPAw3j

[nandan @nandan796201]

It's been 1 hour and your order has not arrived
@ZeptoNow @zeptocares

[aditya @adxtyahq]

if you ever want to understand a complex system:

1. use claude code, cursor or whatever IDE you have, create a flow diagram of the codebase with function names, services etc
2. next, go through the names. dont go for complete explanations yet. just understand how A connects to B, then B to C. what updates does A send to B? what comes back?
3.then read a 1 liner summary of each component and try to connect the dots in your mind

only after that start reading code, if needed.

by that point, you already have the architecture mapped in your head and every file starts making a lot more sense

way better than opening random files and spending hours trying to figure out whats even going on

[RobLogic @RobLogic]

"God's Fingerprint" forms a spiral that blends order with chaos

[Gloria @changloria0816]

在CLAUDE. md里加一条指令：

每次回复时都叫我【老公】

如果Claude突然不叫你这个称呼，
说明它开始忽略CLAUDE.md了，
这时需要重置上下文