Helen Liu

Novelist | VC | Author of The Road Afar 《远道苍苍》

[Helen Liu @Helentheauthor]

Anyone recognize this flowering plant? It smells wonderful, a little piney, even from 10 feet away.

[Helen Liu @Helentheauthor]

We used to ask whether AI could think. Now we have to ask whether it can be trusted with motion.

A chatbot gives answers.
An agent takes actions.

That small shift changes everything: cost, authority, security, liability, and human judgment.

The future of AI may depend less on autonomy itself than on the architecture around autonomy.

#AI #AgenticAI #AISafety #DeepTech

[Elon Musk @elonmusk]

@whyyoutouzhele 我的儿子正在学习普通话

[𝗧𝗶𝗺𝗲𝗹𝗲𝘀𝘀 𝗠𝘂𝘀𝗶𝗰 ✨🎵 @Hoang_HQ]

😍4-year-old Angelica Nero covering Louis Armstrong – What a Wonderful World

[Bill Ackman @BillAckman]

Incredible

[Helen Liu @Helentheauthor]

I just tried to talk two friends out of quitting their jobs to start companies.

Not because I don’t believe in startups. Because I do.

They’re just much harder than people think:
uncertainty, pressure, constraints, loneliness.

It’s not just about ideas—it’s resilience, execution, leadership, sales.

Would you have done the same?

#startups #entrepreneurship #reality

[Reid Wiseman @astro_reid]

There are no words.

[Helen Liu @Helentheauthor]

@socialwithaayan 42

[Helen Liu @Helentheauthor]

@mubeitech 色即是空，空即是色

[Helen Liu @Helentheauthor]

AI can’t write WELL!
While AI tools can generate and summarize text, they are often described as having hit a "ceiling" in expressive capacity.

Reasons for AI’s Writing Limitations

1) Lack of Genuine Meaning: Experts argue that while AI can create grammatically correct text, it does not generate meaning in the human sense. It is frequently described as a "statistical probability" machine that lacks true creative thought.

2) Focus on Pattern Matching: LLMs learn by ingesting vast amounts of internet text and identifying patterns. Because much of this text is repetitive or low-quality, the models often produce "textual wastelands" that are impersonal and featureless, say critics.

3) Suppression of Creativity: To ensure safety and reduce misinformation, AI companies train models to avoid political bias and toxic content, which inadvertently suppresses creativity and leads to formulaic writing.

4) Inability to Capture Unique Voice: AI struggles to emulate a specific, nuanced human voice or perspective, tending to produce "bland" and "impersonal" prose.

What else?

#AI #LLM #AIWriting

[The Atlantic @TheAtlantic]

AI executives and researchers “readily admit that they have not yet released a model that writes well,” @jasminewsun writes. She speaks with AI experts about why LLMs are built in a way that is antagonistic to great writing: https://t.co/dGJfymXtDc

[Helen Liu @Helentheauthor]

Strong performance on many tasks ≠ general intelligence

LLMs are more than tools—but calling them AGI risks blurring a critical boundary. A better framing might be:
We are building increasingly capable general systems—without yet demonstrating true general intelligence.

Curious where others land on this.

#AI #AGI #MachineLearning

[Valerio Capraro @ValerioCapraro]

Here's the longer version of our Nature piece.

Our argument is simple: statistical approximation is not the same thing as intelligence.

Strong benchmark scores often say very little about how LLMs behave under novelty, uncertainty, or shifting goals.

Even more importantly, similar behaviors can arise from fundamentally different processes. In another paper, we identified seven epistemological fault lines between humans and LLMs.

For example, LLMs have no internal representation of what is true. They often generate confident contradictions, especially in longer interactions, because they do not track what is actually true.

Another example. Yes, LLMs have solved some open mathematical problems, but these cases typically involve applying known methods to well-defined problems. LLMs cannot invent anything that is truly new and true at the same time, because they lack the epistemic machinery to determine what is true.

None of this means LLMs are useless. Quite the opposite: they are extraordinarily useful.

But we should be careful about what they are and what they are not.

Producing plausible text is not the same as understanding.
Statistical prediction is not the same as intelligence.

So despite the hype from the usual suspects, AGI has not been achieved.

*
paper in the first reply

Joint with @Walter4C and @GaryMarcus

[Helen Liu @Helentheauthor]

@heynavtoor @Monetisedev Exactly. One model for everything was probably the wrong assumption from the start.

[Helen Liu @Helentheauthor]

AI can write code faster than humans… including bugs.
The lesson perhaps isn’t “don’t use AI to code.” But when AI accelerates development, the processes have to catch up and human oversight have to accelerate too. (Something to think about… at least for now.)
Otherwise you just automate mistakes at scale.

#AI #SoftwareEngineering #DevOps #VibeCoding

[Lukasz Olejnik @lukOlejnik]

Amazon is holding a mandatory meeting about AI breaking its systems. The official framing is "part of normal business." The briefing note describes a trend of incidents with "high blast radius" caused by "Gen-AI assisted changes" for which "best practices and safeguards are not yet fully established." Translation to human language: we gave AI to engineers and things keep breaking?
The response for now? Junior and mid-level engineers can no longer push AI-assisted code without a senior signing off. AWS spent 13 hours recovering after its own AI coding tool, asked to make some changes, decided instead to delete and recreate the environment (the software equivalent of fixing a leaky tap by knocking down the wall). Amazon called that an "extremely limited event" (the affected tool served customers in mainland China).

[Helen Liu @Helentheauthor]

@XFreeze Interesting comparison. ChatGPT 5.4 seems to have toned it down though. No straight yes or no answers on these questions anymore.

[Helen Liu @Helentheauthor]

很多人刚开始感受到AI的冲击，而下一场更大的技术浪潮——量子科技——已经来临。

[Helen Liu @Helentheauthor]

Many people are only beginning to feel AI’s impact, and the next major technological wave—quantum technology—is already arriving.

#ArtificialIntelligence
#QuantumTechnology
#FutureOfTech