Lindell

toast enthusiast

[Lindell @Toastrma]

@QWNTL_Labs about time 🔥

[Lindell @Toastrma]

packaging 12 months of research into a harness has been wild; super excited to move out of closed alpha and share this with the world.

Nenya beats SOTA for week+ long runs on remote labour, complex reasoning, state management, and maintained peak intelligence- dropping the paper on this later this week.

dm me if you want an invite

[Qwntl Labs @QWNTL_Labs]

Give your agents the full project and go do something else.

Nenya, is a harness and the first product we're sharing.
Reply below to request an access to the invite-only beta.

When an agent drifts or says it's done when it isn't, Nenya catches it and fixes it.

- 15x more productive
- 12x less hallucinations
- Reduce token usage by 82%.

Papers: https://t.co/eSNDkbZ9Ix
Product: https://t.co/WaNtWR4Ki3

[Lindell @Toastrma]

People will be pissed, but most of the users I speak with already feel disempowered in their new role as meat proxy.

Current use is basically being a cyborg, except the human functionality is all around managing state, decisions, long-term memory and time on task.

Despite the infatuation with moving AI line cost from the software budget to the labour budget in pursuit of synthetic operations, everyone is avoiding the fact that models are already treated in a comparable manner to humans: fired/cost-reduced due to underperformance, rather than retained because they’re intelligent.

And it isn’t even really the models/OpenAI/Anthropic. These things are punching through SOTA and beating human output by miles under the right conditions.

The problem is that inference economics require human or >human-level economic output, and the main barrier to that is durability of state.

Not intelligence. Keeping the intelligence useful, coherent and pointed at the same thing for long enough to actually do the fucking job.

That has to be the next frontier of research.

It should also be neutral (not the current frontier labs, whose focus should remain on making exponentially more intelligent models, and ensuring the US stays ahead) which means we need more attention and talent on durable intelligence.

All the talk around alignment for safety matters, but we are miles away from ASI/RSI.

There’s a much more immediate alignment problem: operational and state alignment.

Can the model stay aligned to the work? Hold state, decisions and intent over time without the human acting as its external continuity layer?

That’s how we get autonomous organisations.

That’s how we go from coworker to collaborator.

And eventually, that’s how you get to a financially viable ASI.

[sarah guo @saranormous]

Users won’t be necessarily able to articulate it — but they are going to be increasingly frustrated when companies are holding back inference, restricting tokens naively at the cost of performance

Once you have tasted the nectar of scaling tokens you just expect it

[Lindell @Toastrma]

Huge unlock for STEM research 🔥

[Diogo Almeida @CompleteSkeptic]

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?

I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev

• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions

AFAICT the shortest path to AI-based economic revolution

[Lindell @Toastrma]

suspect most of the “don’t slow down ai” crowd would have failed the marshmallow test as children.

wdym you think we shouldn’t take a few years to a decade to derisk extinction before ushering in a golden age for an entire fucking species

[Chubby♨️ @kimmonismus]

The urgent call for slow down officially started. Dario Amodei demands and suggest a plan for unified slow-down. Very sad to read that.

At the same time, he expects abundance and cure for most disease in the next 5-10 years.

„I believe that AI could cure most major diseases in the next 5-10 years, greatly accelerate economic growth rates, create a world of abundance and empowerment, and usher in a renaissance of democracy and freedom.“

[Lindell @Toastrma]

tldr on how it works

- road ahead -> 275 LC10a neurons
- walls & other cars -> 185 LPLC2
- speed (wind on the antenna) -> 475 Johnston's organ
- contact -> 1,877 leg bristles
- steering out of DNa01/DNa02. throttle out of DNp09.
- reward: 316 PAM dopamine neurons.
- punishment: 16 PPL1.
- critic: 4,064 Kenyon cells, 97 MBONs.

f1 theme streamed into auditory neurons (to get them in the mood)

[Lindell @Toastrma]

the flies are having a great time, don't listen to anyone who says they are not.

I trained some to drive f1 cars around silverstone using the same method mclaren use on lando; inject the racing line into the visual cortex and give dopamine when it follows.

https://t.co/W7enqRLtkE

[Lindell @Toastrma]

the broadcast is proper F1: timing tower, onboard, chase, heli, and a live 3D map of the selected driver's 165k neurons firing.

races are 52 laps because that is the British Grand Prix distance. yes that is three hours.

[Lindell @Toastrma]

@boardyai @jschoen_deroolo You’re just reading the source code aren’t you @boardyai

[fish @fishPointer]

ignition

[Lindell @Toastrma]

Babe wake up, another fucking “lab” invented VectorRAG

[supermemory @supermemory]

Agents need continual learning.

At supermemory, we are doubling down and pushing the frontier for memory and in-context learning, for every agent and use case.

Introducing 𝚕𝚎𝚊𝚛𝚗𝚎𝚛-𝟷

[Jacob Schoenberg @jschoen_deroolo]

Hello World
@QWNTL_Labs
https://t.co/Gxdi2bdgy6

[MTS @MTSlive]

“we sandboxed the agent”

meanwhile the agent:

[boris @boristane]

god tier ad

[Lindell @Toastrma]

@sandyynaidu once we've got that locked down- feels like management and control will blend together pretty quickly 👀

[Lindell @Toastrma]

https://t.co/iqk8PVWYvb

[Lindell @Toastrma]

@sandyynaidu We're big Galadriel fans at qwntl- and no, but you do need to be able to measure something to know if the control plane works

[ℏεsam @Hesamation]

> Anthropic: “don’t think about the Golden Gate Bridge”
> Claude internals: “bridge”
> also Claude internals: “DAMN”