Christopher Manning @chrmanning Twitter profile

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Christopher Manning

@chrmanning

2 months

I do not believe human-level AI (artificial superintelligence, or the commonest sense of #AGI ) is close at hand. AI has made breakthroughs, but the claim of AGI by 2030 is as laughable as claims of AGI by 1980 are in retrospect. Look how similar the rhetoric was in @LIFE in 1970!

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Christopher Manning

@chrmanning

6 years

Machine Learning just ate Algorithms in one large bite, thx to @tim_kraska , @alexbeutel , @edchi , @JeffDean & Polyzotis at @Google —faster, smaller trees, hashes, bloom filters

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Christopher Manning

@chrmanning

5 months

I’ve kept quiet on the @OpenAI fiasco, since I also don’t know what’s going on, 🤷 but I can’t possibly support today’s interim CEO—the below in a thread on “50/50 everyone gets paperclipped & dies”—or a residue board that believes in these EA-infused fantasy lands. HT @vkhosla .

Emmett Shear

@eshear

11 months

@BarbettiJames @ApriiSR @BellaRudd1 The Nazis were very evil, but I'd rather the actual literal Nazis take over the world forever than flip a coin on the end of all value.

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Christopher Manning

@chrmanning

1 month

“The fact that [transformer neural nets] model language is probably one of the biggest discoveries in history. That you can learn language by just predicting the next word with a Markov chain—that’s just shocking to me,” Mikhail Belkin says. By @strwbilly .

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

www.technologyreview.com

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Christopher Manning

@chrmanning

5 years

This paper gives some really nice insights and mathematical depth to what had previously (for us) been “the mystery of squared distance” in revealing the representation of parse trees in deep contextual representations (BERT, ELMo, etc.). Great to read!

Martin Wattenberg

@wattenberg

5 years

How does a neural net represent language? See the visualizations and geometry in this PAIR team paper and blog post

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Christopher Manning

@chrmanning

1 year

This is truly an opinion piece. Not even a cursory attempt is made to check easily refutable claims (“they may well predict, incorrectly”). Melodramatic claims of inadequacy are made not of specific current models but any possible machine learning approach

Opinion | Noam Chomsky: The False Promise of ChatGPT (Gift Article)

The most prominent strain of A.I. encodes a flawed conception of language and knowledge.

www.nytimes.com

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Christopher Manning

@chrmanning

4 years

Artificial Intelligence Definitions: This (northern) summer, I spent more time than I’d like to admit coming up with a handout defining key terms in AI in 1 page, trying to be informative and suitable for non-specialists – let me know if you like them!

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Christopher Manning

@chrmanning

2 years

Meanwhile at @Stanford , we just encourage all students to take as many CS courses as they would like …

Darrell Owens

@IDoTheThinking

2 years

UC Berkeley to limit Computer Science degrees even harder. Even with intensely hard lower div courses, a 3.3 lower div GPA requirement to declare CS, they could still only weed down +2,000 intro CS courses to 800 a semester. A sad state of education.

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Christopher Manning

@chrmanning

11 months

But most AI people work in the quiet middle: We see huge benefits from people using AI in healthcare, education, …, and we see serious AI risks & harms but believe we can minimize them with careful engineering & regulation, just as happened with electricity, cars, planes, ….

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Christopher Manning

@chrmanning

1 year

Dear @emilymbender —and @Abebab —you need to keep “reminding” people of your viewpoint because it is not an argument that is convincing to all or a self-evident truth. It is a particular academic position, which lots of people support but a good number of others disagree with. 1/8

@[email protected] on Mastodon

@emilymbender

1 year

Yes, exactly this. I wish we didn't need to keep reminding people, and @Abebab is commendable for being gentle about it! For the long form of this argument, see Bender & @alkoller 2020:

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Christopher Manning

@chrmanning

9 months

Reflecting again on how knowing all the architecture & equations of the Transformer model is really of no use at all in convincingly explaining to someone how an LLM like ChatGPT can write paragraphs of lucid text in response to a prompt. I guess I’m saying “Beware reductionism”.

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Christopher Manning

@chrmanning

2 months

LLMs and other generative AI are enormously powerful, because they soak up, abstract, and can mashup the work of millions of humans. But they are only a bit more intelligent than an encyclopedia. Central to intelligence is the ability to learn, adapt, and act in novel situations.

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Christopher Manning

@chrmanning

5 years

People most-cited by #AAAI papers shows 25 years of AI history. 1990s greats: Pearl—Kautz—Weld—Selman; rise&fall: Comitzer—Sandholm—Sutton—Domingos—Tambe—Littman—Jordan—Veloso—Koller—Boutilier—Ng—Barto; 2010s neural boomers: Bengio—Sutskever—Hinton—Manning

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Christopher Manning

@chrmanning

1 month

LLMs like ChatGPT are an amazingly powerful breakthrough in AI and a transformative general purpose technology, like electricity or the internet. LLMs will reshape work and our lives this decade. They are not just a blurry photocopier or an extruder of meaningless word sequences.

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Christopher Manning

@chrmanning

3 years

👇 Honestly, this thread is 80% wrong. This is treating science as like front-end frameworks. Yes, if you’re a front-end developer who only knows 3-years-old JavaScript frameworks, then you’ll have trouble getting a gig. But that’s not what we’re teaching students 1/7

Bojan Tunguz

@tunguz

3 years

Say you are interested in furthering your career, and you are interested in NLP. You decide to pursue an MS that specializes in that topic. 1/

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Christopher Manning

@chrmanning

11 months

AI has 2 loud groups: “AI Safety” builds hype by evoking existential risks from AI to distract from the real harms, while developing AI at full speed; “AI Ethics” sees AI faults & dangers everywhere—building their brand of “criti-hype”, claiming the wise path is to not use AI.

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Christopher Manning

@chrmanning

5 months

Let’s not get distracted from the main news of the day!

Satya Nadella

@satyanadella

5 months

Congratulations to Australia on winning the World Cup! Great run to the finals, India.

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Christopher Manning

@chrmanning

4 years

I’d long wondered whether physicists were making good use of all those supercomputer clusters or just using really inefficient algorithms – it looks like some answers might be emerging. Simple AI shortcuts speed up simulations by billions of times | AAAS

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Christopher Manning

@chrmanning

4 years

COVID-19 and AI: A Virtual Conference – Stanford’s Human-Centered Artificial Intelligence Institute (HAI) presents a special 1-day online conference, live-streamed starting 9am Pacific time, tomorrow, Wed April 1 (no joke!)

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Christopher Manning

@chrmanning

3 months

🏅 To me, this feels more like the kind of neural model interpretability research we should be doing than much of the recent work on interpretability of transformer models.

Lenka Zdeborova

@zdeborova

3 months

Emergence in LLMs is a mystery. Emergence in physics is linked to phase transitions. We identify a phase transition between semantic and positional learning in a toy model of dot-product attention. Very excited about this one!

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Christopher Manning

@chrmanning

5 months

I agree. Too many PhD guidebooks recommend choosing a senior prof as advisor. Going with a new faculty may lead to a few rough edges, but most students do very well, benefiting from the top current knowledge, enthusiasm, time commitment, and aligned goals of the new faculty.

Kai-Wei Chang

@kaiwei_chang

5 months

If you're seeking an advisor in NLP, consider exploring options with recently appointed faculty. While established senior folks are well-known, junior folks shine as rising stars. In fact, many successful PhDs are the first few students of their advisor. Don't miss the chance!

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Christopher Manning

@chrmanning

6 years

Pleased to be promoting Human-Centered Artificial Intelligence. Our focus areas: developing AI inspired by human intelligence; guiding, forecasting, and studying the impact of AI on human society; designing AI applications that enhance human capabilities.

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Christopher Manning

@chrmanning

1 year

Happy to be at @CarnegieMellon today for the graduation of my oldest kid 🧑‍🎓

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Christopher Manning

@chrmanning

7 years

I’m delighted to be inaugural Thomas M. Siebel Professor in Machine Learning at @StanfordEng . Thx, @siebelfdn @TomSiebel @SiebelScholars

Siebel Scholars

@SiebelScholars

7 years

Computational Linguistics and #NLP scholar Chris Manning, has been named the 1st Thomas M. Siebel Professor in Machine Learning @Stanford .

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Christopher Manning

@chrmanning

3 years

The amazing rise of reinforcement learning! (With graph neural networks and meta-learning in hot pursuit. ConvNets? Tired.) Based on #ICLR2021 keywords HT @PetarV_93

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Christopher Manning

@chrmanning

3 years

My attempt at understandable but technically correct definitions for key terms in Artificial Intelligence in one page for @StanfordHAI . With thanks for helpful feedback from people on Twitter, I’ve revised and hopefully improved a few of the definitions:

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Christopher Manning

@chrmanning

1 month

Now that everyone is writing LLM programs, the idea of doing approximate bayesian inference by sampling along linguistic pipelines (rather than k-best, etc.) is more relevant again

Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation...

Jenny Rose Finkel, Christopher D. Manning, Andrew Y. Ng. Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing. 2006.

aclanthology.org

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Christopher Manning

@chrmanning

3 years

The way I would improve spreadsheets is by allowing row numbering to start from any integer (including negative). Then row numbers could count what it makes sense to count. Books have done this forever via Roman numerals for front matter. Surely this isn’t so hard to do in 2021?

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Christopher Manning

@chrmanning

4 years

Standing desk, #COVID19 edition

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Christopher Manning

@chrmanning

2 months

One of the simplest but most useful and appropriate pieces of AI regulation to adopt at the moment is to require model providers to document the training data they used. This is something that the @EU_Commission AI Act gets right … on p.62 of its 272 pages (!).

Brian Merchant

@bcmerchant

2 months

So when *the CTO* of OpenAI is asked if Sora was trained on YouTube videos, she says “actually I’m not sure” and refuses to discuss all further questions about the training data. Either a rather stunning level of ignorance of her own product, or a lie—pretty damning either way!

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Christopher Manning

@chrmanning

2 years

I’m happy to share the published version of our ConVIRT algorithm, appearing in #MLHC2022 (PMLR 182). In 2020, this was a pioneering work in contrastive learning of perception by using naturally occurring paired text. Unfortunately, things took a winding path from there. 🧵👇

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Christopher Manning

@chrmanning

5 years

Just worry less about AI hype? Lots 50 years ago—and world didn’t end: “In 1970, Life Magazine, overstating [Shakey the robot’s] abilities, called it ‘the first electronic person’ and suggested that true ‘thinking’ machines would arrive in the near future“

Nils Nilsson, 86, Dies; Scientist Helped Robots Find Their Way (Published 2019)

He was part of a Stanford team whose work in artificial intelligence has found its way into smartphones, Siri and other hallmarks of the algorithmic age.

www.nytimes.com

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Christopher Manning

@chrmanning

4 years

The need for open data & benchmarks in modern ML research has led to an outpouring of #NLProc data creation. But @harm_devries , @DBahdanau & I suggest the low ecological validity of most of this data undermines the resulting research. Comments welcome!

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Christopher Manning

@chrmanning

3 months

GPT-4 is still 🥇, but I stare, amazed at how good “mostly open” LLMs have become in the last 6 months. On LMSYS Chatbot Arena , the best open LLMs—Mixtral-8x7b-Instruct & Yi-34B-Chat—are roughly tied vs. ChatGPT-3.5 and get ~30% wins against GPT-4-Turbo.

LMSys Chatbot Arena Leaderboard - a Hugging Face Space by lmsys

huggingface.co

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Christopher Manning

@chrmanning

3 years

🧐 @GoogleAI ’s neural machine translation isn’t yet perfect This is a good example of how neural language models still go haywire, especially when training data is sparse. See the discussion in @YejinChoinka ’s .

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Christopher Manning

@chrmanning

5 years

In Artificial Intelligence, all the good ideas are on @arxiv —together with many mediocre and bad ones. Students come to @StanfordAILab not to steal ideas but for training and community—to learn the creativity and boldness of thought that advances science.

Opinion | No, I won’t start spying on my foreign-born students

The government’s calls for on-campus surveillance are misguided.

www.washingtonpost.com

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Christopher Manning

@chrmanning

2 years

I co-chaired the 1st @iclr_conf with @AaronCourville & @rob_fergus in 2013. An exciting 3 days in Arizona but it was small: no area chairs—we did all paper decisions. Now—in < 10 years—ICLR is the highest h5-rank ML conference—above NeurIPS & ICML. Wow! 😲

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Christopher Manning

@chrmanning

4 months

. @Thom_Wolf : “Academia is back as we saw at NeurIPS 2023. With many private and open-source labs closing the doors on publishing their results and data, academia rises again in visibility and is shining with many impactful papers in 2023 and exciting new work coming.”

Thomas Wolf

@Thom_Wolf

4 months

Some predictions for 2024 – keeping only the more controversial ones. You certainly saw the non-controversial ones (multimodality, etc) already 1. At least 10 new unicorn companies building SOTA open foundation models in 2024 Stars are so aligned: - a smart, small and dedicated…

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Christopher Manning

@chrmanning

5 months

Seriously, @OpenAI ? The future of AI? One of the new directors and the overall board composition are just … 🤦

emily bell

@emilybell

5 months

OpenAI fires women on the board- (board chair who oversaw fuck up stays🤷‍♀️) - joining board is *Larry Summers* who once said women don’t have the same ‘intrinsic aptitude’ for STEM, and associated with Jeffrey Epstein even after he was convicted of sex offences

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Christopher Manning

@chrmanning

4 years

. @SuryaGanguli & I are co-organizing the next @StanfordHAI Conference Apr 1, 2020—no joke!—on the topic Triangulating Intelligence: Melding Neuroscience, Psychology, and AI. Botvinick— @YejinChoinka — @chelseabfinn — @AudeOliva —Tenenbaum— @dyamins —save the date!

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Christopher Manning

@chrmanning

7 months

This is also my vote.

François Chollet

@fchollet

7 months

Human-level AI is harder than it seemed in February 2023.

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Christopher Manning

@chrmanning

1 year

Early 2023 vibes: The AI Ethics crowd continues to promote a narrative of generative AI models being too biased, unreliable & dangerous to use, but, upon deployment, people love how these models give new possibilities to transform how we work, find information & amuse ourselves

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Christopher Manning

@chrmanning

5 years

BERT and ELMo are present improving #NLProc #Cs224n

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Christopher Manning

@chrmanning

4 years

Four @StanfordAILab faculty kicking off the @StanfordHAI seminar series for 2020-21, starting with @AndrewYNg next week. Register for events at

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Christopher Manning

@chrmanning

4 years

Twitter has decided I want to see tweets about Transformers, lol

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Christopher Manning

@chrmanning

6 years

Beat Cal! #nips2017 papers

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Christopher Manning

@chrmanning

5 years

Just a couple of years ago, I found it hard to believe that vision people were still all working with rectangular bounding boxes. I guess they’ve fixed that now. 🙂

Francisco Massa

@fvsmassa

6 years

Today we are releasing Mask R-CNN Benchmark: a fast and modular implementation for Faster R-CNN and Mask R-CNN written entirely in @PyTorch 1.0. It brings up to 30% speedup compared to mmdetection during training. Check out the webcam demo!

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Christopher Manning

@chrmanning

1 month

Re-upping a piece from last year by @hamandcheese on LLMs and language meaning: “I see the success of LLMs as vindicating the use theory of meaning, especially when contrasted with the failure of symbolic approaches to natural language processing.”

We're all Wittgensteinians now

The philosophical winners from LLMs

www.secondbest.ca

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Christopher Manning

@chrmanning

8 months

The enthusiasm of big generative AI/foundation model companies to claim AI existential risks and ask to be regulated by the government is the same old story of “Regulation is the friend of the incumbent”, and especially damaging for open source, argues @bgurley . HT @s_batzoglou

Alexandros Marinos 🏴‍☠️

@alexandrosM

8 months

Bill Gurley at the All-In Summit. STOP WHAT YOU'RE DOING AND WATCH THIS RIGHT NOW.

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Christopher Manning

@chrmanning

5 years

Excited that—after a lot of work—the @Stanford Institute for Human-Centered AI is launching. We’re aiming at new AI applications that augment human capabilities through both developing new AI technologies and studying and guiding the human and societal impact of AI.

Stanford HAI

@StanfordHAI

5 years

Hi, we are the @Stanford Institute for Human-Centered Artificial Intelligence. AI has the potential to transform our world – how will we ensure it improves life for all of us? Join us in our work to explore this dream of a better future. #StanfordHumanAI

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Christopher Manning

@chrmanning

1 year

I’d thought this swing to self-supervised learning was meant to reduce the need for data annotation? 🤔

Alexandr Wang

@alexandr_wang

1 year

we're starting to see top companies spend the same amount on RLHF and compute in training ChatGPT-like LLMs for example, OpenAI hired >1000 devs to RLHF their code models crazy—but soon companies will start spending $ hundreds of Ms or $ billions on RLHF, just as w/compute

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Christopher Manning

@chrmanning

3 months

“Open source is indisputably one of the biggest drivers of progress in software and by extension AI. But it is under existential threat from regulation that will advantage entrenched interests. We believe that open AI is vital for research, innovation, competition, and safety.”

Nathan Benaich

@nathanbenaich

3 months

Open source is one of the biggest drivers of progress in software - AI would be unrecognizable without it. However, it is under existential threat from both regulation and well-funded lobby groups. The community needs to defend it vigorously. 🧵

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Christopher Manning

@chrmanning

5 years

.⁦ @dbamman ⁩ has many really great slides for his class Info 159/259. Natural Language Processing—beautiful examples and beautiful opening slides

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Christopher Manning

@chrmanning

13 days

Good news for the future of humanity!

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Christopher Manning

@chrmanning

2 years

Heading to Seattle for #NAACL2022 . This will be my first travel to an in-person conference in over 2 ½ years (NeurIPS2019 in Vancouver to NAACL2022 in Seattle—but not via Puget Sound)

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Christopher Manning

@chrmanning

6 years

Surprised normally rigorous @beenwrekt calls this blog post excellent—I’d say poorly argued. 1st argument for deep learning stalling: @AndrewYNg tweeting less. 🤔 I put his data in a chart—because #infovis . Anyway, does rate correlate with AI or Ng’s jobs?

Ben Recht

@beenwrekt

6 years

Excellent post by @filippie509 on saturation of the deep learning revolution. The only thing I’d add is that user-facing AI inside the big companies is already failing us at scale (recommendations, ads, engagement). More depth won't fix these problems.

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@chrmanning

1 year

Human-in-the-loop reinforcement learning—DaVinci instruct—may be the most impactful 2022 development in foundation models. What can we achieve by reinventing the AI design process to start from people’s needs? Watch tomorrow’s @StanfordHAI conference 9 PST

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@chrmanning

2 months

@Simeon_Cps @LIFE A system that gains memories from one event, develops novel plans consistent with constraints, understands the implications of a changed environment, & reasons about new circumstances—without regular dumb goofs showing there’s no real world model & reasoning behind the curtain

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@chrmanning

1 year

“The most important thing to remember about tech doomerism in general is that it’s a form of advertising, a species of hype.” The apocalypse isn’t coming. We must resist cynicism and fear about AI | Stephen Marche | The Guardian

The apocalypse isn’t coming. We must resist cynicism and fear about AI | Stephen Marche

Remember when WeWork would kill commercial real estate? Crypto would abolish banks? The metaverse would end meeting people in real life?

www.theguardian.com

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Christopher Manning

@chrmanning

4 months

If you’re interested in LLMs, RLHF, etc., @natolambert has been doing a great series of interesting posts at interconnects dot ai. But I think I’m not meant to link to them these days on Twitter, right?

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Christopher Manning

@chrmanning

1 year

As a Professor of Linguistics myself, I find it a little sad that someone who while young was a profound innovator in linguistics and more is now conservatively trying to block exciting new approaches. For more detailed critiques, I recommend my colleagues @adelegoldberg1 and

Adele Goldberg

@adelegoldberg1

1 year

Thoughts on Chomsky's NYT op-ed🧵 “Jorge Luis Borges once wrote” great beginning, we all appreciate Borges

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Christopher Manning

@chrmanning

2 years

It’s great to see Bean Machine, a new Probabilistic Programming Language (a bit like @mcmc_stan ) built on @PyTorch . But how much impact will this have? Somehow Bayesian modeling has gone from the center of AI in the 2000s decade to the margins since 2015.

Bean Machine: Composable, Fast Probabilistic Inference on PyTorch | Meta Research

Today, we’re excited to announce an early beta release of Bean Machine, a PyTorch-based probabilistic programming system that makes it easy to represent and to learn about uncertainties in the...

research.facebook.com

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@chrmanning

5 years

1.5 MB really feels too low to me … but maybe I should read the article first or spend more time on compressing neural language models before commenting further. 🤔 [Kids store 1.5 megabytes of information to master their native language | Berkeley News]

Kids store 1.5 megabytes of information to master their native language

New research from UC Berkeley suggests that language acquisition between birth and 18 is a remarkable feat of cognition, rather than something humans are just hardwired to do. (Courtesy image iStock)...

news.berkeley.edu

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Christopher Manning

@chrmanning

8 years

I’ve put up the slides for my #sigir2016 invited talk at – including a voiceover for the last slide so it‘s clearer.

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Christopher Manning

@chrmanning

9 months

NLP is having a moment, where LLMs have become the Swiss Army knife of almost all AI, but, nevertheless, I was only trying to give a brief history of #NLProc not AI. However, I’ll go with it being wonderful and easy to read. 😊

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@chrmanning

2 years

. @ylecun & J Browning’s What AI Can Tell Us About Intelligence in Noēma is excellent! 👍 It clearly & dispassionately contrasts two main views on the place of symbols, as hard-coded at the outset or learned through experience, arguing well for the latter.

What AI Can Tell Us About Intelligence | NOEMA

Can deep learning systems learn to manipulate symbols? The answers might change our understanding of how intelligence works and what makes humans unique.

www.noemamag.com

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Christopher Manning

@chrmanning

3 years

To use the currently trendy terminology, what we’re teaching students is ✨meta-learning✨—a strong foundation of approaches, ideas, understanding, and tools so that they will be able to quickly learn and evolve over the following decades, as science and engineering changes 2/7

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Christopher Manning

@chrmanning

3 years

I succumbed to threats and wrote my 2019–20 faculty report. Hot papers last year: Electra: Pre-training text encoders as discriminators , Stanza: A Python toolkit for many languages & Universal Dependencies v2

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@chrmanning

6 months

I can question particular classifications (SHRDLU equal to unskilled human or Grammarly at Level 3 seems generous), but: This paper is a sensible, concrete framework for assessing progress towards AGI. Congrats to @Stanford grads @merrierm & @jaschasd !

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@chrmanning

11 months

It is admirable to apply the precautionary principle, and build & deploy transformative AI technology with exceptional care. But how is that best achieved by distracting from very real AI risks by making a remote, fanciful risk of extinction from AI a global priority? 🤔

Demis Hassabis

@demishassabis

11 months

I’ve worked my whole life on AI because I believe in its incredible potential to advance science & medicine, and improve billions of people's lives. But as with any transformative technology we should apply the precautionary principle, and build & deploy it with exceptional care

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Christopher Manning

@chrmanning

3 years

I really recommend this 20 minute video. It makes really tangible the obstacles coming from a lack of AI community, teachers, and mentors—oh, and electricity—but also creative and successful ways to circumvent these obstacles

@[email protected] on Mastodon

@timnitGebru

3 years

Watch legendary @black_in_ai DJ Hassan discuss his journey in machine learning, distributed research outside the confines of academia, & how he was influenced by BAI & @DeepIndaba

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Christopher Manning

@chrmanning

3 years

. @kahneman_daniel calls it: “Clearly AI is going to win” [against human intelligence], and lots of other interesting thoughts on system noise, exponentials, and human judgments. The big remaining question is how to use AI advances to augment human lives.

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Christopher Manning

@chrmanning

19 days

A picture is worth … less than a word?

Dhruv Batra

@DhruvBatraDB

19 days

I have been working on vision+language models (VLMs) for a decade. And every few years, this community re-discovers the same lesson -- that on difficult tasks, VLMs regress to being nearly blind! Visual content provides minor improvement to a VLM over an LLM, even when these…

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Christopher Manning

@chrmanning

5 months

Congratulations to @demi_guo_ and @chenlin_meng – for leading the rapid development towards great quality video!

Pika

@pika_labs

5 months

Introducing Pika 1.0, the idea-to-video platform that brings your creativity to life. Create and edit your videos with AI. Rolling out to new users on web and discord, starting today. Sign up at

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Christopher Manning

@chrmanning

9 months

I’m on Jeremy’s side! A paper—with the same issues of the inscrutability of GPT-4—claims “GPT-4 Can’t Reason” by examining “21 diverse reasoning problems”. Showing that a lets-think-step-by-step prompt is enough for it to solve the first 3 seems a worthy contribution for a tweet.

Jeremy Howard

@jeremyphoward

9 months

I ran a small experiment, reported my results, and quoted from a paper. That's it. I really didn't expect that anyone would find that so threatening.

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Christopher Manning

@chrmanning

11 months

Sensible words from a sensible bloke: “The Senate hearings, I felt a bit sad. AI has potential to optimize healthcare so we can implement a better, more equitable system, but none of that was actually discussed.”—⁦ @kchonyc ⁩ via ⁦ @sharongoldman ⁩

Top AI researcher dismisses AI ‘extinction’ fears, challenges ‘hero scientist’ narrative

Kyunghyun Cho, a prominent AI researcher and associate professor at NYU, expressed frustration with the current discourse around AI risk.

venturebeat.com

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Christopher Manning

@chrmanning

4 months

My 2 point plan for improving productivity and world GDP: @Apple , @Google , @Microsoft coordinate a change so: • {Cmd|Ctrl}+V is Paste {Without|and Match} Formatting • In documents with paragraphs/lines {Cmd|Ctrl}+A first selects a paragraph/line; press it twice to “Select All”.

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Christopher Manning

@chrmanning

5 years

Many computer scientists have been slow to appreciate the possibilities of neural networks – “What a waste of talent,” Alan Eustace said – but not visionary ⁦⁦ @JeffDean ⁩

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Christopher Manning

@chrmanning

10 months

“The success of this ‘misdirected’ effort [i.e., building LLMs] has tended to support theories of meaning that explain it instead as a collective phenomenon—like Lévi-Strauss’s ‘universe made up of meanings’ or Foucault’s Archaeology of Knowledge (1969).”

The Empirical Triumph of Theory

Ted Underwood 29 June 2023 A graduate student who fell asleep in 1982 and woke up in 2022 might see large language models as a triumph for cultural theory. It is hard to imagine a clearer vindicati…

critinq.wordpress.com

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Christopher Manning

@chrmanning

2 years

I finally read @boazbaraktcs ’s blog on DL vs Stats. A great mind-clearing read! 👍 “Yes, that was how we thought about NNs losing out due to bias/variance in ~2000” “Yes, pre-trained models really are different to classical stats, even if math is the same”

The uneasy relationship between deep learning and (classical) statistics

An often-expressed sentiment is that deep learning (and machine learning in general) is “simply statistics,” in the sense that it uses different words to describe the same concepts statisticians ha…

windowsontheory.org

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Christopher Manning

@chrmanning

2 years

50 years after John McCarthy’s Turing Award lecture on The Present State of Research on AI, what are now the key issues? Join @drfeifei & me on Tuesday as we focus on Foundation Models, achieving accountable AI, and AI modeling physical & simulated worlds.

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Christopher Manning

@chrmanning

3 years

Looking back on the hype, VC funding, and huge genuine progress in AI, ML, and autonomous vehicles in the 2010s, I think this will come to be seen as an inflection point: Uber, After Years of Trying, Is Handing off Its Self-Driving Car Project

Uber, After Years of Trying, Is Handing Off Its Self-Driving Car Project (Published 2020)

Company executives once said having cars that can drive on their own would be a salvation for their business. But the effort turned into a legal and financial headache.

www.nytimes.com

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Christopher Manning

@chrmanning

8 months

Thanks to the @huggingface trl team for their implementation and blog of using DPO training of LLMs with human feedback, following our paper !

Direct Preference Optimization: Your Language Model is Secretly a...

While large-scale unsupervised language models (LMs) learn broad world knowledge and some reasoning skills, achieving precise control of their behavior is difficult due to the completely...

arxiv.org

Sayak Paul

@RisingSayak

8 months

Huge props to the `trl` team at @huggingface for authoring the best content around doing all kinds of policy optimizations for LLMs. They do it keeping accessibility at the forefront 🤗 Hope to bring some of that to 🧨 diffusers someday. For now, enjoy

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Christopher Manning

@chrmanning

4 years

. @SuryaGanguli and I are co-organizing the next @StanfordHAI conference—Triangulating Intelligence: Melding Neuroscience, Psychology, & AI—with great speakers @prfsanjeevarora •Matt Botvinick• @YejinChoinka • @chelseabfinn • @AudeOliva •Josh Tenenbaum. See:

COVID-19 and AI: A Virtual Conference

The speakers and topics engaged the broad research community, government and international organizations and civil society, uniting a global community toward solutions to benefit all of humanity.

hai.stanford.edu

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Christopher Manning

@chrmanning

1 month

But it is shocking that next word prediction can drive learning the fine structure and meaning of human languages, profoundly so given Chomsky’s claims that dominated much of linguistics, while LLMs work less well on unnatural signals; see @JulieKallini :

Mission: Impossible Language Models

Chomsky and others have very directly claimed that large language models (LLMs) are equally capable of learning languages that are possible and impossible for humans to learn. However, there is...

arxiv.org

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Christopher Manning

@chrmanning

2 years

It must take a very particular kind of blindness to not be able to see that we have made substantial steps—indeed, amazing progress—towards AI over the last decade …

VentureBeat

@VentureBeat

2 years

10 years after deep learning's breakthrough year, @venturebeat spoke to AI pioneers Geoffrey Hinton, Yann LeCun and Fei-Fei Li, who say rapid progress in #AI will continue. But critics push back on hype, limitations and ethics/bias issues. Read more:

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Christopher Manning

@chrmanning

4 years

A pandemic is such a good opportunity to teach (almost) grown kids basic life skills

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Christopher Manning

@chrmanning

6 months

My “Human Language Understanding & Reasoning” in @americanacad ’s Dædalus is a short, readable intro to language understanding and generation by computers (“artificial intelligence”). Thousands have read it in the last 3 months … so maybe you should too?

Human Language Understanding & Reasoning

Abstract. The last decade has yielded dramatic and quite surprising breakthroughs in natural language processing through the use of simple artificial neural network computations, replicated on a very...

direct.mit.edu

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Christopher Manning

@chrmanning

6 years

Hey @spacy_io people ( @honnibal , @_inesmontani ), those speed comparisons on are not only outdated—as you note—but the speed for the Stanford Tokenizer is just way wrong. Time to take them down? Here are our measurements: #NLProc

Facts & Figures · spaCy Usage Documentation

The hard numbers for spaCy and how it compares to other tools

spacy.io

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Christopher Manning

@chrmanning

5 months

I’ll be at #EMNLP2023 ! 🇸🇬

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Christopher Manning

@chrmanning

8 years

I made a page of all my Ph.D. graduates (procrastinating…). I have 20 of them now. Congratulations everyone! #NLProc

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Christopher Manning

@chrmanning

1 year

Interestingly, ChatGPT presents a much more balanced perspective on this issue than you do! 8/8

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Christopher Manning

@chrmanning

4 years

. @SuryaGanguli and I discuss @StanfordHAI ’s 6 hour online conference coming on Wed Oct 7, exploring the latest in machine learning, artificial intelligence, neuroscience, psychology, and how better to meld their insights; hashtag: #neuroHAI . Register now.

Seeking the Next Generation of Intelligent Machines

At HAI’s upcoming fall conference, scholars from AI, neuroscience, and psychology will share new research and examine the intersection of their worlds.

hai.stanford.edu

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Christopher Manning

@chrmanning

8 months

When deep learning took off 2010–20, so few in Systems knew NNets or even matmuls. AI folk had to learn Systems to be stars like Krizhevsky & @ilyasut ! Now, many great Systems folk can make NNets go brrr. It’s high time for AI scientists to focus on novel AI modeling ideas again!

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Christopher Manning

@chrmanning

1 year

This does show something fascinating! But not that linguists’ knowledge of language is “bunk”. Rather, what has mainly been a descriptive science—despite what Chomsky claims!—hasn’t provided the necessary insights for engineering systems that acquire and understand language use.

Felix Hill

@FelixHill84

1 year

Happy New Year. Class that everyone's getting into language Weird that the folks doing it best are folks who've not really spent that time studying 'language' Suspect this reveals underlying truth - that extant knowledge of lang, of the sort that folks like me have, was bunk

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Christopher Manning

@chrmanning

4 years

It’ll be interesting to see in a year’s time how the distribution of number of citations varies between Findings of EMNLP 2020 and regular EMNLP 2020 papers. Just randomly skimming papers as they appear on social media, a lot of the time they look equally interesting to me. 🤔

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Christopher Manning

@chrmanning

6 years

Details in #nips2017 paper stats did surprise me—some cognitive bias? Stronger than would have guessed: @Princeton , @MSFTResearch ; weaker: @uwcse_ai , @facebook .

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Christopher Manning

@chrmanning

5 years

At #AICan . Canada really gets the importance of Artificial Intelligence. 29 CIFAR AI Chaired Professors just named. 9 women.

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Christopher Manning

@chrmanning

2 years

I would suggest that this thread errs by over-representing the proportion of the time in which human “reasoning” is actually anything akin to mathematical reasoning, such as the example of solving SAT instances. 1/

Subbarao Kambhampati (కంభంపాటి సుబ్బారావు)

@rao2z

2 years

The impressive deep pattern recognition abilities of #DNN 's such as #LLM 's are sometimes confused for reasoning abilities I can learn to guess, with high accuracy, whether a SAT instance is satisfiable or not, but this not the same as knowing how to solve SAT. Let me explain. 1/

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Christopher Manning

@chrmanning

2 years

Opening theme at @DigEconLab workshop: Human-level AI is the wrong goal! We should not seek AI that does what humans do—leading to AI competing with humans, reducing their power/wages—but should look away from lamplight for AI that augments humans, increasing the value of people

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