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Josh Wolfe Profile picture
@wolfejosh
Aug 11, 2021 • 9 tweets • 3 min read • Read on X
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More from @wolfejosh

Josh Wolfe Profile picture
Oct 23
1/ why Quantum is BULLSHIT

"paving a path towards potential future"

like saying: 'Working towards possibility of maybe a thing that might one day be a breakthrough if a breakthrough were to maybe occur'

Here I assemble just 2005 to 2015 annual headlines or this BULLSHIT
2/ I could start in the 90s. But let's just go thru 20yrs of BULLSHIT

2005... Image
3/ 2006... Image
Read 18 tweets
Josh Wolfe Profile picture
Oct 8
1/ Revealing Lux's latest

a $101M launch of new cutting-edge biotech created from one the most important scientific breakthrus Lux has seen in many yrs!

NILO

control IMMUNE system 🦠
via NERVOUS system 🧠...

we stealth funded last yr before this NATURE paper got published👇Image
Image
2/ THE BIG IDEA?

Your brain has a direct hotline to your immune system.

Specific neurons in the vagus nerve detect inflammatory signals + then tell your brainstem to dial inflammation up or down.

When our team cut this connection immune responses went completely haywire!
3/ Here's HOW it works:

Think: biological thermostat for inflammation🌡️

Different vagal neurons respond to pro vs anti inflammatory cytokines (proteins that act as messengers in cell communication)

They relay this info to neurons––which then regulate the immune response...
Read 7 tweets
Josh Wolfe Profile picture
Aug 21
1/ Apple researchers just dropped NEW foundation model on BEHAVIORAL data from wearables.

Forget raw sensors—think steps, heart variability, gait

Trained on 2.5B hours via 162K people

Predicts age, sex, pregnancy, sleep like a crystal ball. Image
2/ Their new foundation model (WBM) trained not on noisy low-level sensor data––but on derived behavioral metrics via wearables

Outperforms raw sensor models in predicting sleep, injury, & infection.

When combined CRUSH it—predicting pregnancy w/ >90% accuracy. Image
3/ Contrarian take––Transformers may be overkill for everything

head-to-head on wearable data (Mamba-2) beat Transformers for health prediction. Simpler tokenization also won.

Lesosn: data’s unique physics (irregular, noisy)+ ignore the loud signals to hear the whispers––edge is in the architectureImage
Image
Read 4 tweets
Josh Wolfe Profile picture
Aug 21
1/ New Lux quarterly LP letter––Q2 2025

theme: “Friction Frontier”

-Over 50% of small VCs will involuntarily exit as ~5 VCs are planning to voluntarily exit (IPO)

-Lux team has invested over half a billion dollars across 82 companies (new + existing) in the past few months… Image
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2/
-Zuck’s “ Poachapalooza 2025”

-L&A (License + Acquihire) is the new M&A

-the AI capex surge (5% of GDP) ~ fiber-optic + router binge of 2000 tech boom (5.2%) and short step below sheet-rock bonanza of 2005 housing bubble (6.7%).

-Open source vs Closed… Image
3/great irony in frenzy for ARTIFICIAL intelligence––what’s acquired isnt hardware but HUMAN intelligence

-frontier of agentic Al not defined by model size-but what we can verify

-99% reliable agent degrades to 60.5% after 50 sequential decision tasks––each error cascading like cracks in glassImage
Read 8 tweets
Josh Wolfe Profile picture
Aug 18
1/ Beyond the hype + headlines

some eye-opening AI stats to consider

Today Mag 7 = 35% of US stock mkt value

NVDA = 19% of that––and 42% of NVDA revenue comes from just 5 Big Tech co's buying GPUs:

Meta, Amazon, Microsoft, Google, Tesla
2/At recent lunch with LP who put Lux in business I talked about shift from consensus cloud inference (GPUs + datacenters + power) to on-device inference (memory + batteries)...
3/ This valued LP talked about CAPEX:

Meta, AMZN, MSFT, GOOG TLSA spending $560B by EOY 2025

The total AI revenue from that spend? ~$35B

That's not great ~6% return
Read 5 tweets
Josh Wolfe Profile picture
Jun 7
Apple just GaryMarcus'd LLM reasoning ability Image
2/ Apple tested today's "reasoning" AIs like Claude + DeepSeek which look smart—but when complexity rises, they collapse.

Not fail gracefully. Collapse completely.
3/ They found LLMs don't scale reasoning like humans do.

They think MORE up to a point…

Then they GIVE UP early, even when they have plenty of compute left.
Read 6 tweets

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