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Erik Craddock
Erik Craddock@eriklink

Surprisingly large number of people may have marker for tick-linked meat allergy

The findings suggest far more Americans than previously thought may be at risk of the allergy, which can make having a hamburger for dinner a potentially life-threatening choice. The Centers for Disease Control and Prevention has previously estimated that only 0.14 percent of the US population (up to 450,000 people) has the allergy. But the study also highlights how little we understand about this unique disease—and the challenges of accurately diagnosing it.

Surprisingly large number of people may have marker for tick-linked meat allergy

Ars Technica

Surprisingly large number of people may have marker for tick-linked meat allergy

There's still a slew of questions about why some people develop alpha-gal syndrome.

linkvia Ars Technica
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Erik Craddock
Erik Craddock@eriklink

Understanding the Dynamics of the AI Ecosystem with Pace Layers

This is why you can go to the AI Engineering World’s Fair and come away thinking everyone is building dark factories and automating entire enterprises, while non-developers from outside the greater-San Francisco AI complex wonder why data centers are necessary.

Understanding the Dynamics of the AI Ecosystem with Pace Layers

Drew Breunig

Understanding the Dynamics of the AI Ecosystem with Pace Layers

Stewart Brand’s Pace Layers framework reveals why AI’s speed is straining the slower systems it depends on for support.

linkby Drew Breunigvia Drew Breunig
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Erik Craddock
Erik Craddock@eriklink

Import AI 464: Fables writes GPU kernels; AI automation; and analog computation

What happens to online employment when this reaches 80%? Of course, some new tasks will get created – people will innovate and find tasks that they can do which AI systems can’t do. But how many of these new tasks will exist? Enough to replace the labor the AI systems now do? It’s increasingly hard for me to reconcile the continued progress of AI systems with the economy staying the same – rather, it’s more likely to me we are about to see extremely person-light AI-heavy (or person-nil) organizations expand to take over chunks of the economy, out-competing un-augmented humans.

Import AI 464: Fables writes GPU kernels; AI automation; and analog computation

Import AI

Import AI 464: Fables writes GPU kernels; AI automation; and analog computation

Welcome to Import AI, a newsletter about AI research. Import AI runs on arXiv, cappuccinos, and feedback from readers. If you’d like to support this, please subscribe. Subscribe now Fable writes a …

linkby Jack Clarkvia Import AI
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Erik Craddock
Erik Craddock@eriklink

The Problem is Prompt Debt

The first symptom of prompt debt is slowing iteration. As users flag errors and spot edge cases, additional guidance is added to the instructions, nudging the model into line. If unwanted behaviors persist, instructions are repeated, with increasing severity. Pretty soon, the prompt isn’t straightforward and quick fixes regress previous instructions. Errors can no longer be handled with one-line “hot fixes” and your development cycle slows to a crawl.

The Problem is Prompt Debt

Drew Breunig

The Problem is Prompt Debt

The plain-English prompt that makes prototypes effortless turns out to be a poor way to specify how a system should behave, and the bill arrives slowly, disguised as ordinary progress, until the application can barely move.

linkby Drew Breunigvia Drew Breunig
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Erik Craddock
Erik Craddock@eriklink

Import AI 462: Superpersuasion; self-sustaining AI; paths to ASI

“Our findings establish frontier AI as a more capable conversational persuader than the most prepared, incentivized, and expert humans we could recruit. Training humans does not appear to close that gap,” they write. “As access to these systems continues to grow, the question is no longer whether AI can out-persuade humans but how, where, and on whose behalf this capability will be exercised.”

Import AI 462: Superpersuasion; self-sustaining AI; paths to ASI

Import AI

Import AI 462: Superpersuasion; self-sustaining AI; paths to ASI

Welcome to Import AI, a newsletter about AI research. Import AI runs on arXiv, cappuccinos, and feedback from readers. If you’d like to support this, please subscribe. Subscribe now AI can decisive…

linkby Jack Clarkvia Import AI
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Erik Craddock
Erik Craddock@eriklink

SaaS is dead; long live SaaS!

That era of building a viable SaaS business in a few months is gone. I mean, it technically still exists today but only in the arbitrage sense that the rest of the world hasn’t yet caught on to how quickly and easily software can be built. It’ll be gone soon, I promise.

Jamie’s blog

SaaS is dead; long live SaaS!

How AI has changed the SaaS equation: what’s no longer valuable, and what remains

link
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Erik Craddock
Erik Craddock@eriklink

There Are No Instances in atproto — overreacted

In atproto, every app is a projection of the whole Atmosphere, just like Feedly and Google Reader are projections of the entire Blogosphere. You mostly “decentralize” by swapping your hosting, and/or by making and trying new apps. Running many full copies of the Bluesky database server is possible, but it’s not any more useful than running many copies of Google Reader.

There Are No Instances in atproto — overreacted

overreacted.io

There Are No Instances in atproto — overreacted

Like RSS and Google Reader.

link
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Erik Craddock
Erik Craddock@eriklink

The future of the con is already here, it's just not evenly distributed

Here’s a partial list of scam-relevant capabilities that LLMs have that would previously require significant skilled human effort per target:

Researching a mark to find out the best way to go after them.
Personally tailoring all communication with a mark in mind, dynamically adjusting based on how they respond to various approaches.
Cloning the voice of a person the mark trusts, like a relative.
Plausible, real-time deepfaking of a video call.
Building a plausible-looking corroborating fake web presence 6.
Realtime monitoring of compromised resources, and dynamically building up the scam based on this monitoring.
Better triage and discovery of marks.
Avoiding signature-detection based spam filters (shown by Heiding et al).
Scanning for and chaining known exploits in unpatched deployed software. Mass scanning isn’t new, but cheaply building tooling that can keep tabs on the latest CVEs and learn new tricks is7.

These are capabilities that exist today, and they’ll only improve from here. We should look at these skills as a floor, not a ceiling.

The future of the con is already here, it

manishearth.github.io

The future of the con is already here, it

The Set-Up Johnny Hooker: Sometime after 2:00, a guy’s gonna call on that phone there and give you the name of a horse. Imagine yourself, perhaps a …

link
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