I really enjoyed writing this one. Protocols like @centrifuge and @OndoFinance are changing the game. 🔥
For DeFi to make a fundamental difference in finance, it must address the sea of value that currently exists in TradFi ✨
In our latest #Binance Insights & Analysis report, we explore how real world assets (RWAs) such as real estate, stocks, and bonds, are being brought on-chain to be used in DeFi.
Topics:
🔸 How do RWAs work?
🔸 RWA markets
🔸 Top RWA protocols
And more ⬇️
https://t.co/2jHQ2eve9l
The energy around @Bittensor at @proofoftalk was exceptional.
We had great conversations with old friends and made plenty of new ones across the ecosystem.
People are no longer asking whether Bittensor can attract builders. They're asking how subnets will take market share, generate revenue, and build sustainable advantages over centralized AI firms.
The ecosystem feels materially different than it did a year ago: more serious teams, stronger infrastructure, more capital, and significantly higher conviction.
Came away more bullish than ever on SN14 Cacheon and the broader Bittensor space.
Still a long road ahead, but the momentum is undeniable. Hopefully more good news in the coming weeks.
Cacheon competition restarts June 1. What we overhauled this week:
- One-pass eval: speed + correctness on the same prompts, same outputs
- Single metric: end-to-end wall time vs baseline (no TTFT / TPS split)
- Improved logging and telemetry
- Emissions ramp up after June 8
- Conviction lock soon
Inference is the compute layer everything runs on. Open competition is how we surface the best. Miners, show us what you've got. 💪
Read more: https://t.co/xZE4ZtjTVW
We shipped two things over the weekend: a 0.1 TAO miner submission fee and @shadeformai GPU support.
Submission fee: Every on-chain commit now costs 0.1 TAO. Goal is to cut spam and add skin in the game. Fee covers GPU rental first; anything left buys SN14 tokens and burns it. Miner workflow is unchanged. Docs: https://t.co/IfKldbyBTh
Shadeform GPUs: Validator can now pull GPUs from Shadeform alongside @TargonCompute and @lium_io
for evaluations. More supply, less wait time.
Updates on evaluation upgrade coming later this week. Follow our Bittensor Discord channel for ongoing discussions.
The “it’s not AGI because machine intelligence is jagged” is dumb cope.
It’s obviously AGI. If you had a friend who had a 130 IQ, could write production code flawlessly, could write academic papers of a high research caliber, pass any exam in any field with flying colors, create a sophisticate LBO model, draw technical diagrams perfectly, compose poetry in any language, and could find solutions to significant unsolved mathematical problems, you would call that person a world historical genius. Certainly, no single human has ever had intelligence that “general” before.
Now you think it’s “not AGI” because it sometimes slips up and makes mistakes - so does any human that you would consider “extraordinarily intelligent.”
The professor might forget a colleagues name that he has known for a decade. He is still considered intelligent. The math genius might be a little autistic and shy, unable to maintain polite conversation. Still intelligent. You might stare at the fridge for 30 seconds unable to find the butter, despite 5 million years of evolution perfecting your visual intelligence.
We give intelligent humans a pass when they have jagged intelligence. So why the double standard?
The qualities people list as “necessary for AGI” are important traits to have, but no longer pertain to intelligence. People will say things like “true AGI requires agency, long term goal setting, embodiment, self-direct action”.
But none of those things are intelligence. Those are “things that humans have that AI lacks”. Raw intelligence, AI has it in spades. That other stuff - important yet, but broader than and different from intelligence.
The unwillingness of people to acknowledge that AGI obviously exists and has existed for a while is due to a kind of anthropic chauvinism - a psychological need to believe that humans are superior in every respect, that we possess soft skills that no machine could replicate.
Yes humans are different from machines, but if we are limiting the discussion solely to general intelligence, AI has it already. That battle is over.
If you want to reframe the discussion to matters of human dignity and personhood, fine, but that’s not an AGI question. That’s something else. Just take the loss on AGI already. It’s over.
Passive S&P 500 funds could have to buy roughly 19% of public SpaceX shares within 6mo under fast-tracking framework (it would enter the index at the est 6th spot), Russell 1000 and Nasdaq 100 may buy another 5.5% within weeks of the IPO. Thrown in active MFs benchmarked to those indices and you get to HALF of SpaceX shares. Nice study from my colleague @rduboff
So Jane Street is going public because obviously they see the future where the model labs compete directly with them in the market.
The strategic decision is therefore to become a a specialized infrastructure harness for a future frontier model.
Tellingly they point out that the latency constraints mean there is no time for inference at the GPU layer, or agentic tool use at the CPU layer, only reflexive heuristics at the FPGA layer.
@yminsky is trying to fend off future model lab competition by making Jane Street indispensable to a future AGI.
interesting strategy
Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.
Cacheon mainnet is live.
13 inference servers queued, each racing to beat our baseline on a dedicated 8x H200 pod.
The winner earns up to $10,000/day. Inference optimization starts today on @Bittensor.
Follow along: https://t.co/u52cmcD3Hb
With compute and energy resources constrained, model edge will increasingly be attributed to inference techniques rather than scaling compute.
Cacheon is elevating the problem set of the next phase of model performance.
@xavi3rlu and Cacheon gigabrains have my full attention
Launching Cacheon: an open, incentivized competition for LLM inference optimization.
As model quality converges, the next frontier is serving them economically at scale: lower latency, higher throughput, and lower cost per token.
Cacheon turns that problem into a live arena with continuous evaluation. Developers submit containerized inference servers, benchmarked on standardized hardware against a pinned vLLM baseline. The fastest server that preserves output correctness wins.
The goal is to make better inference systems discoverable, measurable, deployable, and rewarded in the open.
Mainnet launches by May 19. Learn more: https://t.co/JPbyJpLszq
$QQQ is now trading 9.8 ATRs above the 50 SMA
This has literally never happened before in the history of the QQQ ETF since its inception in March 1999.
We are truly in uncharted territory!
Today we are launching two revolutionary products: Dual and Phase.
These devices will enhance how humans dream.
Prophetic Dual retails for $449 and starts shipping at the end of this year.
Prophetic Phase retails for $1299 and starting shipping middle of next year.