2025 UPDATE!! AMZN MSFT slash jobs!! AI blackmails! Altman: prepare for AI to be "uncomfortable"…33% jobs gone…BASIC INCOME?

bnew

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Duolingo will replace contract workers with AI​


The company is going to be ‘AI-first,’ says its CEO.

by Jay Peters

Apr 28, 2025, 7:47 PM EDT

Allen & Company Annual Conference Draws Media And Tech Leaders To Sun Valley


Duolingo co-founder and CEO Luis von Ahn. Photo: Getty Images

Jay Peters is a news editor covering technology, gaming, and more. He joined The Verge in 2019 after nearly two years at Techmeme.

Duolingo will “gradually stop using contractors to do work that AI can handle,” according to an all-hands email sent by co-founder and CEO Luis von Ahn announcing that the company will be “AI-first.” The email was posted on Duolingo’s LinkedIn account.

According to von Ahn, being “AI-first” means the company will “need to rethink much of how we work” and that “making minor tweaks to systems designed for humans won’t get us there.” As part of the shift, the company will roll out “a few constructive constraints,” including the changes to how it works with contractors, looking for AI use in hiring and in performance reviews, and that “headcount will only be given if a team cannot automate more of their work.”

von Ahn says that “Duolingo will remain a company that cares deeply about its employees” and that “this isn’t about replacing Duos with AI.” Instead, he says that the changes are “about removing bottlenecks” so that employees can “focus on creative work and real problems, not repetitive tasks.”

Related​



“AI isn’t just a productivity boost,” von Ahn says. “It helps us get closer to our mission. To teach well, we need to create a massive amount of content, and doing that manually doesn’t scale. One of the best decisions we made recently was replacing a slow, manual content creation process with one powered by AI. Without AI, it would take us decades to scale our content to more learners. We owe it to our learners to get them this content ASAP.”

von Ahn’s email follows a similar memo Shopify CEO Tobi Lütke sent to employees and recently shared online. In that memo, Lütke said that before teams asked for more headcount or resources, they needed to show “why they cannot get what they want done using AI.”

Here’s the text of von Ahn’s memo from Duolingo’s LinkedIn post:

]

I’ve said this in Q&As and many meetings, but I want to make it official: Duolingo is going to be AI-first.

AI is already changing how work gets done. It’s not a question of if or when. It’s happening now. When there’s a shift this big, the worst thing you can do is wait. In 2012, we bet on mobile. While others were focused on mobile companion apps for websites, we decided to build mobile-first because we saw it was the future. That decision helped us win the 2013 iPhone App of the Year and unlocked the organic word-of-mouth growth that followed.

Betting on mobile made all the difference. We’re making a similar call now, and this time the platform shift is AI.

AI isn’t just a productivity boost. It helps us get closer to our mission. To teach well, we need to create a massive amount of content, and doing that manually doesn’t scale. One of the best decisions we made recently was replacing a slow, manual content creation process with one powered by AI. Without AI, it would take us decades to scale our content to more learners. We owe it to our learners to get them this content ASAP.

AI also helps us build features like Video Call that were impossible to build before. For the first time ever, teaching as well as the best human tutors is within our reach.

Being AI-first means we will need to rethink much of how we work. Making minor tweaks to systems designed for humans won’t get us there. In many cases, we’ll need to start from scratch. We’re not going to rebuild everything overnight, and some things-like getting AI to understand our codebase-will take time. However, we can’t wait until the technology is 100% perfect. We’d rather move with urgency and take occasional small hits on quality than move slowly and miss the moment.

We’ll be rolling out a few constructive constraints to help guide this shift:

We’ll gradually stop using contractors to do work that AI can handle

AI use will be part of what we look for in hiring

AI use will be part of what we evaluate in performance reviews

Headcount will only be given if a team cannot automate more of their work

Most functions will have specific initiatives to fundamentally change how they work

All of this said, Duolingo will remain a company that cares deeply about its employees. This isn’t about replacing Duos with AI. It’s about removing bottlenecks so we can do more with the outstanding Duos we already have. We want you to focus on creative work and real problems, not repetitive tasks. We’re going to support you with more training, mentorship, and tooling for AI in your function.

Change can be scary, but I’m confident this will be a great step for Duolingo. It will help us better deliver on our mission — and for Duos, it means staying ahead of the curve in using this technology to get things done.

--Luis

 
Last edited:

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Audible is giving publishers AI tools to quickly make more audiobooks​


Publishers will be able to choose from over 100 AI-generated voices in English, Spanish, Italian, and French.
by Andrew Liszewski

May 13, 2025, 2:18 PM EDT
12 Comments12 New

If you buy something from a Verge link, Vox Media may earn a commission. See our ethics statement.
The Audible logo on a black, orange, and cream background.


Illustration by Alex Castro / The Verge
Andrew Liszewski is a senior reporter who’s been covering and reviewing the latest gadgets and tech since 2006, but has loved all things electronic since he was a kid.

Amazon’s Audible has announced that it’s planning to expand its audiobook catalog by giving select publishers access to its new “fully integrated, end-to-end AI production technology” that will let them more easily convert titles to audiobooks with their choice of AI-generated voices. The initiative will also help expand global access to audiobooks with the introduction of a new AI translation tool that’s expected to launch in an early beta later this year.

Audible says its new AI narration technology leverages Amazon’s advanced AI capabilities and will be made available to interested publishing partners in the coming months in one of two ways. For publishers wanting to be hands-off, an end-to-end service managed by Audible handles the “entire audiobook production process” right up to publication, while a self-service option will give publishers access to the same tools so they can independently direct the entire production process.

With both options, publishers are able to “choose from a quickly growing and improving selection of more than 100 AI-generated voices across English, Spanish, French, and Italian with multiple accent and dialect options, and will be able to access voice upgrades for their titles as our technology evolves,” according to Amazon.

Last September, Amazon invited a select group of Audible narrators to train AI-generated voice clones of themselves ahead of the launch of this new service. The company said that if their AI voice replica was selected for a project, the narrators would be able to review the final audiobook for errors or inaccuracies and use the platform’s production tools to fine-tune pronunciations or adjust the pacing of their voice.

Audible’s upcoming AI translation tools will also be limited to select publishers, and will initially support translations from English to Spanish, French, Italian and German. As with audiobook production, publishers will be offered two different approaches. Text-to-text translation for manuscripts which can be later turned into audiobooks, and speech-to-speech translation which uses AI to preserve the “original narrators’ voice and style across languages.”

Publishers will also be able to review translations themselves or opt for a human review through Audible with a professional linguist.
 

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LLMs Struggle with Real Conversations: Microsoft and Salesforce Researchers Reveal a 39% Performance Drop in Multi-Turn Underspecified Tasks​


By Nikhil

May 16, 2025

Conversational artificial intelligence is centered on enabling large language models (LLMs) to engage in dynamic interactions where user needs are revealed progressively. These systems are widely deployed in tools that assist with coding, writing, and research by interpreting and responding to natural language instructions. The aspiration is for these models to flexibly adjust to changing user inputs over multiple turns, adapting their understanding with each new piece of information. This contrasts with static, single-turn responses and highlights a major design goal: sustaining contextual coherence and delivering accurate outcomes in extended dialogues.

A persistent problem in conversational AI is the model’s inability to handle user instructions distributed across multiple conversation turns. Rather than receiving all necessary information simultaneously, LLMs must extract and integrate key details incrementally. However, when the task is not specified upfront, models tend to make early assumptions about what is being asked and attempt final solutions prematurely. This leads to errors that persist through the conversation, as the models often stick to their earlier interpretations. The result is that once an LLM makes a misstep in understanding, it struggles to recover, resulting in incomplete or misguided answers.

AD_4nXcUVipGgOjoqnMYmS4e0WYdz27UAQnIzHn_Xy7bo5ioMmoi1EKIdLNxCHfpFu8JibE4JoEYCPxDcsaACRZqZ8RxrUG4Q7cL6Ys0ou9rYZGfIjOkQzOmqDQQv4AiI86h6HL4_mQ


Most current tools evaluate LLMs using single-turn, fully-specified prompts, where all task requirements are presented in one go. Even in research claiming multi-turn analysis, the conversations are typically episodic, treated as isolated subtasks rather than an evolving flow. These evaluations fail to account for how models behave when the information is fragmented and context must be actively constructed from multiple exchanges. Consequently, evaluations often miss the core difficulty models face: integrating underspecified inputs over several conversational turns without explicit direction.

Researchers from Microsoft Research and Salesforce Research introduced a simulation setup that mimics how users reveal information in real conversations. Their “sharded simulation” method takes complete instructions from high-quality benchmarks and splits them into smaller, logically connected parts or “shards.” Each shard delivers a single element of the original instruction, which is then revealed sequentially over multiple turns. This simulates the progressive disclosure of information that happens in practice. The setup includes a simulated user powered by an LLM that decides which shard to reveal next and reformulates it naturally to fit the ongoing context. This setup also uses classification mechanisms to evaluate whether the assistant’s responses attempt a solution or require clarification, further refining the simulation of genuine interaction.

AD_4nXdT1ruLcTssCpOuhB38sOH-ZeZLzVdQTCaJnrr9TdKtezyQGoY6pJ4aI-ZSfMCEju6Kvo1WLrY0PEb09VIbs5uQEYjRv0P6hz6GHKZZjUCLmQ7D8itY_57UBQ291XfpzVEYNTT4NQ


The technology developed simulates five types of conversations, including single-turn full instructions and multiple multi-turn setups. In SHARDED simulations, LLMs received instructions one shard at a time, forcing them to wait before proposing a complete answer. This setup evaluated 15 LLMs across six generation tasks: coding, SQL queries, API actions, math problems, data-to-text descriptions, and document summaries. Each task drew from established datasets such as GSM8K, Spider, and ToTTo. For every LLM and instruction, 10 simulations were conducted, totaling over 200,000 simulations. Aptitude, unreliability, and average performance were computed using a percentile-based scoring system, allowing direct comparison of best and worst-case outcomes per model.

Across all tasks and models, a consistent decline in performance was observed in the SHARDED setting. On average, performance dropped from 90% in single-turn to 65% in multi-turn scenarios—a 25-point decline. The main cause was not reduced capability but a dramatic rise in unreliability. While aptitude dropped by 16%, unreliability increased by 112%, revealing that models varied wildly in how they performed when information was presented gradually. For example, even top-performing models like GPT-4.1 and Gemini 2.5 Pro exhibited 30-40% average degradations. Additional compute at generation time or lowering randomness (temperature settings) offered only minor improvements in consistency.

AD_4nXeCr-yyIPogtmJ7umQXn5H0d0jo7VBf8bMzrulhe4Cw-OhaWxCGIi-ubmwOLXrpHYVm-1nzkRbLKMb3gMycTWV-2Gq_vUwNa8Ob0NdT7g58v3vc_69gi7gYDavde8O3LUkcrzeVJA


This research clarifies that even state-of-the-art LLMs are not yet equipped to manage complex conversations where task requirements unfold gradually. The sharded simulation methodology effectively exposes how models falter in adapting to evolving instructions, highlighting the urgent need to improve reliability in multi-turn settings. Enhancing the ability of LLMs to process incomplete instructions over time is essential for real-world applications where conversations are naturally unstructured and incremental.




Check out the Paper and GitHub Page . All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 90k+ ML SubReddit .

 

bnew

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1/1
🆔 ashlynnb.bsky.social
attorneys who are getting sanctioned for using ChatGPT would beg to differ

[QUOTED POST]
🆔 wired.com
Anthropic CEO Dario Amodei said everything human workers do now will eventually be done by AI systems. www.wired.com/story/anthro...
bafkreied5pvrn2h6hfsk46fa6zk7zjpj2aegkg4khybdu6cqznigznykia@jpeg


To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196

1/35
🆔 wired.com
Anthropic CEO Dario Amodei said everything human workers do now will eventually be done by AI systems. www.wired.com/story/anthro...
bafkreied5pvrn2h6hfsk46fa6zk7zjpj2aegkg4khybdu6cqznigznykia@jpeg


2/35
🆔 dark-eyed-junco.bsky.social
The word “eventually” doing some very heavy lifting here, like so heavy you wonder if it is even news

3/35
🆔 jizzwiz.bsky.social

bafkreiedq76dfmphnlilacrxswk7oyerlqhvpagijfidjfzwrxvokmnqk4@jpeg


4/35
🆔 markwatson1989.bsky.social
Will the last human consumer please turn the lights off on the economy?

What will AI be purchasing to prop up the current economic model?

5/35
🆔 brettshady.bsky.social
Ha! Id like to see them master staring blankly at the corner of a computer screen while they wonder where the past 20 years of their life went…

Checkmate, AI!

6/35
🆔 darthwaiter.bsky.social
If all human work is replaced by AI then who will actually pay for it?

7/35
🆔 darth2024.bsky.social
Is it AI fundraising season again?

8/35
🆔 kevinriggle.bsky.social
It's always AI fundraising season

9/35
🆔 drbirdman.bsky.social
Every statement like this from a CEO reads like “salesman swears his new product will change your life”

10/35
🆔 bradiscranky.bsky.social
how can your coverage of the admin be so good and your coverage of industry so bad

11/35
🆔 ringogreat.bsky.social
But I was hoping to assemble iPhones when I retire.

12/35
🆔 tomtacoma.bsky.social
What about being CEO? I am sure AI could his company better

13/35
🆔 preraphsrule.bsky.social
Really? Like caregiving, for example?

14/35
🆔 amydentata.bsky.social
Cute ad pitch, how's the revenue stream coming along

15/35
🆔 kungfuarcade.com
Okay AI, fix my ice maker.

16/35
🆔 kalax.me
eventually is a pretty loose timeline.

17/35
🆔 bluevoter65.bsky.social
I'm old enough to remember being told in 80's that by 2000 we would work 20 hours per week because technology would be doing so much of our jobs. Flash forward to 2025, I work in IT, and I struggle to keep up with the workload.

I'll believe that when I see it.

18/35
🆔 ebrillhart.bsky.social
Wonder if he has a financial incentive to say that

19/35
🆔 stillwellgray.ca
does he know he's a worker

20/35
🆔 dont-get-played.bsky.social
It is all just fantasy and children's toys until they make a robot that can empty the dishwasher.

21/35
🆔 johngosland.bsky.social
Absolutely love Wired - but yalls PR and Human Resource management of him and his sisters image in the newest mag almost had me un subbed.

Reading for over 10 years and I’m still shocked yall ran that story.

Is there any disclosure over if Anthropic paid for that article? It’s unbelievable

22/35
🆔 dodgytheories.bsky.social
But right now now they can't even make a piece of toast. I'm not holding my breath.

23/35
🆔 joejinis.bsky.social
That's what technology was supposed to be.
How it ended?
It costs way less money to have cheap slaves doing all the work than expensive robots.

24/35
🆔 jholderness.bsky.social
bsky.app/profile/eve6...

[QUOTED POST]
🆔 eve6.bsky.social
"Ai is coming for your jobs". I'd like to see ai take a southwest flight with 3 layovers to open for hoobastank at a county fair

25/35
🆔 techviews.bsky.social
Great. Start with the dumb ass CEOs then.

26/35
🆔 littlenomad.bsky.social
This will doom the world unless governments are prepared to offer all their citizens a guaranteed basic income.

27/35
🆔 majorb.bsky.social
Eventually a thousand beautiful women will show up at my doorstep and ask if they can watch anime with me

28/35
🆔 twincitieschick.bsky.social
I'll believe it when AI can make me a sandwich.

29/35
🆔 flatline42.bsky.social
Have to say "sudo make me a sandwich" for it to work.

xkcd.com/149/
bafkreiciptc5jjl7x3fvmk4qv6nrjgmao5teyx6f37xu3n7pzcyajjlhcm@jpeg


30/35
🆔 max-chillax.bsky.social
Crock o shyt

31/35
🆔 basildegres.bsky.social
Every street merchant shouts his wares

32/35
🆔 flatline42.bsky.social
Anthropic needs you to believe that and keep shoving billions into it's stochastic parakeet software.

33/35
🆔 robinparkerlaw.bsky.social
And this is good because…..???

34/35
🆔 alifeinretail.bsky.social
If all the human workers don't have jobs, where will the rich folk get money from?

35/35
🆔 hwbrgdtse.bsky.social
Yeah this time it's going to be revolutionary, for totally, you guys.

To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
 

bnew

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Kylie Robison
Business

May 23, 2025 1:16 PM

Inside Anthropic’s First Developer Day, Where AI Agents Took Center Stage​


Anthropic CEO Dario Amodei said everything human workers do now will eventually be done by AI systems.
Anthropic CEO Dario Amodei gestures as he addresses the audience as part of a session on AI during the World Economic...


Anthropic CEO Dario Amodei.Photo-Illustration: WIRED Staff; PHotograph: FABRICE COFFRINI/Getty Images

Anthropic’s first developer conference kicked off in San Francisco on Thursday, and while the rest of the industry races toward artificial general intelligence, at Anthropic the goal of the year is deploying a “virtual collaborator” in the form of an autonomous AI agent.
“We're all going to have to contend with the idea that everything you do is eventually going to be done by AI systems,” Anthropic CEO Dario Amodei said in a press briefing. “This will happen.”

AI Lab Newsletter by Will Knight​


WIRED’s resident AI expert Will Knight takes you to the cutting edge of this fast-changing field and beyond—keeping you informed about where AI and technology are headed. Delivered on Wednesdays.

By signing up, you agree to our user agreement (including class action waiver and arbitration provisions), and acknowledge our privacy policy.

As roughly 500 attendees munched breakfast sandwiches with an abnormal amount of arugula, and Anthropic staffers milled about in company-issued baseball caps, Amodei took the stage with his chief product officer, Mike Krieger.
“When do you think there will be the first billion-dollar company with one human employee?” Krieger asked. Amodei, wearing a light-gray jacket and a pair of Brooks running shoes, replied without skipping a beat: “2026.” (Later in the press lounge, a spokesperson said they dub this version of Amodei “professor panda” due to his casual-professional attire and his love for pandas—his Slack profile picture is him with a stuffed panda.
Image may contain Mike Krieger Electrical Device Microphone Clothing Footwear Shoe People Person Adult and Crowd


Photograph: Don Feria/AP Images

There’s a common company line you’ll hear about agents, and Krieger got to it quickly: They won’t replace employees, just help human workers with tasks. “They're moving from just being engineers to being managers of several autonomous agents, tackling everything from a simple coding task to complex, full-stack development projects across multiple code bases,” Krieger said. “It took our technical onboarding time to get engineers up to speed from two to three weeks to two to three days.”

It’s a belief echoed by Anthropic’s top brass. Cofounder Jack Clark has said he expects people to “manage fleets of AI agents,” while Amodei says he believes software engineers are necessary (for now) to guide models. Still, as the models get more capable in areas from coding to creative writing, it certainly seems like redundancies are imminent.
“I think we're just at the beginning of what we can do with the new generation of model in terms of tasks,” Amodei said, noting that he’s particularly excited about Opus’ ability to aid in cybersecurity and biomedical research.

Anthropic is making a big push into biomedical research, offering up to $20,000 in API credits to researchers in biology and genetics. “We have found that the [new] model’s abilities in biology are substantially better,” Amodei said in a press briefing. This has contributed to Claude Opus 4’s Chemical, Biological, Radiological, and Nuclear risk level, making it the highest risk model Anthropic has released to date based on its Responsible Scaling Policy.
Anthropic CEO Dario Amodei  and Chief Product Officer Mike Krieger unveil Claude 4 during the Code with Claude...


Anthropic CPO Mike Krieger

Photograph: Don Feria/AP Images
Image may contain Andreas Hestler People Person Crowd Adult Clothing Hat Architecture Building and Classroom


Anthropic CEO Dario Amodei

Photograph: Don Feria/AP Images

After the morning keynote, journalists were ushered from the dark auditorium to a sunny deck upstairs, and I went to scavenge for snacks and doodads—I got a handful of Anthropic magnets and a tote bag that says “Code w/ Claude.” After an hour of media gossip and diet cokes, we headed back down for a press briefing with Amodei (who skipped into his chair) and Krieger.

In March, Amodei had said that “90 percent of code” will be written by AI within the next six months. So I was curious to ask both executives how much of Anthropic's code is currently written by Claude.
“Something like over 70 percent of [Anthropic’s] pull requests are now Claude code written,” Krieger told me. As for what those engineers are doing with the extra time, Krieger said they’re orchestrating the Claude codebase and, of course, attending meetings. “It really becomes apparent how much else is in the software engineering role,” he noted.

The pair fiddled with Voss water bottles and answered an array of questions from the press about an upcoming compute cluster with Amazon (Amodei says “parts of that cluster are already being used for research,”) and the displacement of workers due to AI (“I don't think you can offload your company strategy to something like that,” Krieger said).

We’d been told by spokespeople that we weren’t allowed to ask questions about policy and regulation, but Amodei offered some unprompted insight into his views on a controversial provision in President Trump’s megabill that would ban state-level AI regulation for 10 years: “If you're driving the car, it's one thing to say ‘we don't have to drive with the steering wheel now.’ It's another thing to say ‘we're going to rip out the steering wheel, and we can't put it back in for 10 years,’” Amodei said.

What does Amodei think about the most? He says the race to the bottom, where safety measures are cut in order to compete in the AI race.
“The absolute puzzle of running Anthropic is that we somehow have to find a way to do both,” Amodei said, meaning the company has to compete and deploy AI safely. “You might have heard this stereotype that, ‘Oh, the companies that are the safest, they take the longest to do the safety testing. They're the slowest.’ That is not what we found at all.”
Image may contain Cup Disposable Cup Kitchen Utensil and Ladle


Photograph: Don Feria/AP Images
Image may contain Scott Barry Kaufman People Person Backpack Bag Adult Airport Clothing Hat and Crowd


Photograph: Don Feria/AP Images
Anthropic-SF-Business-DF200256.jpg


Photograph: Don Feria/AP Images

After an array of journalist-exclusive fireside chats with Anthropic’s top researchers, including researcher and philosopher Amanda Askell, cofounder Chris Olah, and researcher Jan Leike, attendees poured out of the event center into Waymos and Ubers or waited around for the after-party.

What I heard from Krieger on Wednesday, and from a spokesperson at the conference, is that the company decided to throw this conference now because it’s finally a big enough company to host one.

The company has doubled in size in the past year to 1,300 employees and is valued at a whopping $61.5 billion. For a company that once positioned itself as the careful cousin in a reckless industry, Anthropic seems ready to step into the spotlight—and eager to host the party.
 

bnew

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1/11
@AngryTomtweets
It's over.

This is Dyna, and it's coming for your job.

Dyna runs 24/7, folding, fixing, hustling through the dirty work without flinching.

This isn’t just automation—it’s a new industrial era...

https://video.twimg.com/amplify_video/1923761544174895108/vid/avc1/1280x720/Tm4VvX1nnDBinoNi.mp4

2/11
@AngryTomtweets
Introducing Dynamism v1 (DYNA-1) by /DynaRobotics & /JasonMa2020

Affordable, Easy-to-Deploy Autonomous AI Robots.

Dyna

https://video.twimg.com/amplify_video/1923761610281320459/vid/avc1/1280x720/aCrS2Ur6kxB_vdd1.mp4

3/11
@AngryTomtweets
DYNA-1 is battle-tested to upscale-restaurant standards.

In a 24-hour run, it folded 850+ napkins autonomously, sustaining ~60% of human speed while holding a 99.4% success rate—zero interventions, full shift reliability.

https://video.twimg.com/amplify_video/1923761865009893376/vid/avc1/1280x720/TXzx2JT4rLSCXJCE.mp4

4/11
@AngryTomtweets
Most robots fail at basic manipulation. DYNA-1 doesn’t. This isn’t about napkins. It’s about autonomy at scale.

- Pulls one napkin from a stack
- Adapts to out-of-distribution edge cases
- Transfers skills to laundry folding, cup filling & more

https://video.twimg.com/amplify_video/1923762121713795072/vid/avc1/1280x720/9HoFvqQo_MWZRdS-.mp4

5/11
@AngryTomtweets
More here:

Dyna

6/11
@AngryTomtweets
That's a wrap!

If you enjoyed this thread:

1. Follow me /AngryTomtweets for more of these
2. RT the tweet below to share this thread with your audience

https://video.twimg.com/amplify_video/1923761544174895108/vid/avc1/1280x720/Tm4VvX1nnDBinoNi.mp4

7/11
@CaptainHaHaa
No dramas, No HR issues just solid work in exchange for a steady stream of electricity and the occasional maintenance.

8/11
@MeeraAIIT
Dyna out here working harder than half the startup world

9/11
@heyrobinai
is it coming for my job too? haha

10/11
@shushant_l
The future of work just got a serious upgrade.

11/11
@Ryan_DeQuiroz
I’m ready for Dyna. That’s all I’ve wanted out of AI and robotics - for it to do my laundry. I’ll risk combat with it when it goes rogue. The cost/benefit analyses says “go”.


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GnauzBookOfRhymes

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That folding robot speaks to me.

I’d pay a monthly fee or buy one outright if they can keep it under $1,500 with a solid warranty.
 

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[Research] AI System Completes 12 Work-Years of Medical Research in 2 Days, Outperforms Human Reviewers



Posted on Thu Jun 19 13:28:36 2025 UTC

/r/OpenAI/comments/1lfau5l/ai_system_completes_12_workyears_of_medical/

Harvard and MIT researchers have developed "otto-SR," an AI system that automates systematic reviews - the gold standard for medical evidence synthesis that typically takes over a year to complete.

Key Findings:

Speed: Reproduced an entire issue of Cochrane Reviews (12 reviews) in 2 days, representing ~12 work-years of traditional research
Accuracy: 93.1% data extraction accuracy vs 79.7% for human reviewers
Screening Performance: 96.7% sensitivity vs 81.7% for human dual-reviewer workflows
Discovery: Found studies that original human reviewers missed (median of 2 additional eligible studies per review)
Impact: Generated newly statistically significant conclusions in 2 reviews, negated significance in 1 review

Why This Matters:

Systematic reviews are critical for evidence-based medicine but are incredibly time-consuming and resource-intensive. This research demonstrates that LLMs can not only match but exceed human performance in this domain.

The implications are significant - instead of waiting years for comprehensive medical evidence synthesis, we could have real-time, continuously updated reviews that inform clinical decision-making much faster.

The system incorrectly excluded a median of 0 studies across all Cochrane reviews tested, suggesting it's both more accurate and more comprehensive than traditional human workflows.

This could fundamentally change how medical research is synthesized and how quickly new evidence reaches clinical practice.

https://www.medrxiv.org/content/10.1101/2025.06.13.25329541v1.full.pdf
 
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