James Duez

Precise, deterministic and explainable AI for enterprise-grade applications. Co-Founder and CEO at

[James Duez @jamesduez]

Automation bias is a deep cognitive challenge for humans. We cannot consistently check LLM generated outputs. Human in the loop is not enough.

[Anne Applebaum @anneapplebaum]

Amazing: KPMG wrote a report describing the successful use of AI by businesses. But the case studies turned out to be AI hallucinations.
https://t.co/s3LE8vedNi

[Anne Applebaum @anneapplebaum]

Amazing: KPMG wrote a report describing the successful use of AI by businesses. But the case studies turned out to be AI hallucinations.
https://t.co/s3LE8vedNi

[Optalysys @Optalysys]

privacy won’t scale on luck — predictable encrypted compute is the real unlock

[Gary Marcus @GaryMarcus]

Not saying this *is* the crash, but it is what the opening moments of a crash would look like.

[Sully @SullyOmarr]

so let me get this right:

Oracle says Openai committed $300B for cloud compute → oracle stock jumps 36% (best day since 1992)

Oracle runs on Nvidia GPUs → has to buy billions in chips from Nvidia

Nvidia just announced they're investing $100B into openai

Openai uses that money to... pay oracle... who pays Nvidia... who invests in Openai

[Gary Marcus @GaryMarcus]

“Gary Marcus calls the belief in LLM understanding one of ‘the most profound illusions of our time’"

[James Duez @jamesduez]

@VentureBeat When LLMs are outside their training zone, they don’t get worse at thinking… they reveal they were never thinking at all. We need neurosymbolic approaches that are grounded in logic, not just language.
@RainbirdAI

[James Duez @jamesduez]

When LLMs are outside their training zone, they don’t get worse at thinking… they reveal they were never thinking at all. We need neurosymbolic approaches that are grounded in logic, not just language. @RainbirdAI

[VentureBeat @VentureBeat]

LLMs generate 'fluent nonsense' when reasoning outside their training zone https://t.co/yNOdBBigrA

[James Duez @jamesduez]

@ericmitchellai @sama It is not precise, deterministic and auditable - the attributes required for high stakes applications where there is zero tolerance for error. Precise reasoning is not generalisable. LLMs are a piece in the neurosymbolic puzzle, but knowledge needs to be a first class citizen.

[Gonto 🤓 @mgonto]

The saddest thing on my day is that @GaryMarcus is right.

I hate it!

[Gary Marcus @GaryMarcus]

Sorry!!

If it makes you feel better, it’s a sad day for a lot of people.

[Ewan Morrison @MrEwanMorrison]

"the best move may be to completely avoid relying on AI chatbots to provide factual information."

IMHO - AI companies have a problem they can't fix but rather than admit it & risk a crash, they've pushed their faulty tech into as many companies & govt systems as possible.

[Carlo Edoardo Ferraris @carloAI]

6/ Anthropic isn’t chasing consumers it’s betting on businesses.

While Google integrates with Gmail and OpenAI powers ChatGPT.

Anthropic’s focus is different:

Build the best API for enterprise use.

Quietly becoming the backbone of AI in business.

[Gary Marcus @GaryMarcus]

All the tech bros this morning thinking that AGI has been achieved because some (insanely expensive) new form of LLMs can now match top *high school students* on one specific task … it’s almost … cute! ☺️

[James Duez @jamesduez]

Check out my latest article: Reality Check: What Apple's Study Tells Us About "Reasoning Models" https://t.co/xSRX28E3rP

[Ruben Hassid @rubenhassid]

BREAKING: Apple just proved AI "reasoning" models like Claude, DeepSeek-R1, and o3-mini don't actually reason at all.

They just memorize patterns really well.

Here's what Apple discovered:

(hint: we're not as close to AGI as the hype suggests)

[James Duez @jamesduez]

I just published "Automation Bias and the Deterministic Solution: Why Human Oversight Fails AI" https://t.co/itoJhAJaAr

[Anthropic @AnthropicAI]

New Anthropic research: Do reasoning models accurately verbalize their reasoning?

Our new paper shows they don't.

This casts doubt on whether monitoring chains-of-thought (CoT) will be enough to reliably catch safety issues.