Meta released AI research to push the boundaries of machine intelligence (AMI)
1. Meta Perception Encoder. Powering advanced computer vision for tasks like image recognition and object detection.
2. 3D Scene Understanding. Smarter AI that can locate objects from natural language queries.
3. Collaborative Reasoner. A framework to boost the reasoning skills of large language models, paving the way for collaborative AI agents.
These open-source advancements bring us closer to machines that perceive and decide like humans.
1. Meta Perception Encoder. Powering advanced computer vision for tasks like image recognition and object detection.
2. 3D Scene Understanding. Smarter AI that can locate objects from natural language queries.
3. Collaborative Reasoner. A framework to boost the reasoning skills of large language models, paving the way for collaborative AI agents.
These open-source advancements bring us closer to machines that perceive and decide like humans.
Meta AI
Advancing AI systems through progress in perception, localization, and reasoning
Meta FAIR is releasing several new research artifacts that advance our understanding of perception and support our goal of achieving advanced machine intelligence (AMI).
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The_state_of_AI_1745227157.pdf
5.4 MB
McKinsey's Latest State of AI Report: Organizations Are Finally Moving From Experimentation to Value Creation
The March 2025 State of AI report is out, and it captures a pivotal moment in AI adoption. Here's what's most significant:
A few takeaways:
β’ 78% of organizations now use AI in at least one business function (up from 72% in early 2024)
β’ 71% regularly use generative AI (up from 65% six months ago)
β’ Only 21% have fundamentally redesigned workflows to incorporate gen AI - but these organizations are seeing the most value
The report highlights what separates organizations that are creating value from those still experimenting:
CEO-level oversight of AI governance has the strongest correlation with bottom-line impact
Workflow redesign - not just technology adoption - is critical for value creation
Tracking specific KPIs for AI solutions drives measurable results
Workforce Impact:
β’ AI skills shortage is easing: fewer organizations report difficulty hiring AI talent compared to previous years
β’ 53% of C-level executives regularly use gen AI at work (vs. 44% of middle managers)
β’ 38% predict gen AI will have little effect on workforce size in the next 3 years
While progress is significant, over 80% of organizations still don't see material impact on enterprise-level EBIT from gen AI. This underscores that we're still in the early stages of this transformation.
The March 2025 State of AI report is out, and it captures a pivotal moment in AI adoption. Here's what's most significant:
A few takeaways:
β’ 78% of organizations now use AI in at least one business function (up from 72% in early 2024)
β’ 71% regularly use generative AI (up from 65% six months ago)
β’ Only 21% have fundamentally redesigned workflows to incorporate gen AI - but these organizations are seeing the most value
The report highlights what separates organizations that are creating value from those still experimenting:
CEO-level oversight of AI governance has the strongest correlation with bottom-line impact
Workflow redesign - not just technology adoption - is critical for value creation
Tracking specific KPIs for AI solutions drives measurable results
Workforce Impact:
β’ AI skills shortage is easing: fewer organizations report difficulty hiring AI talent compared to previous years
β’ 53% of C-level executives regularly use gen AI at work (vs. 44% of middle managers)
β’ 38% predict gen AI will have little effect on workforce size in the next 3 years
While progress is significant, over 80% of organizations still don't see material impact on enterprise-level EBIT from gen AI. This underscores that we're still in the early stages of this transformation.
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Nari Labs released Dia, a SOTA open-source text-to-speech model
Built with zero funding, the 1.6B param AI supports emotional tones, multiple speakers, and nonverbal cues
Plus, it beats leaders like ElevenLabs Sesame.
GitHub
HuggingFace
Waitlist.
Built with zero funding, the 1.6B param AI supports emotional tones, multiple speakers, and nonverbal cues
Plus, it beats leaders like ElevenLabs Sesame.
GitHub
HuggingFace
Waitlist.
GitHub
GitHub - nari-labs/dia: A TTS model capable of generating ultra-realistic dialogue in one pass.
A TTS model capable of generating ultra-realistic dialogue in one pass. - nari-labs/dia
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Researchers introduced Robotic Tactile Simulation
Taccel Simulator is a high-performance simulation platform for vision-based tactile sensors and robots.
Boosted by Nvidia Warp, researchers optimized Taccel with highly parallelized simulations and support 900fps simulation with 4k+ parallel training envs.
Taccel is designed with user-friendly APIs and is easy to use. Open-sourced all the code and documentation.
Preprint
Code
Taccel Simulator is a high-performance simulation platform for vision-based tactile sensors and robots.
Boosted by Nvidia Warp, researchers optimized Taccel with highly parallelized simulations and support 900fps simulation with 4k+ parallel training envs.
Taccel is designed with user-friendly APIs and is easy to use. Open-sourced all the code and documentation.
Preprint
Code
arXiv.org
Taccel: Scaling Up Vision-based Tactile Robotics via...
Tactile sensing is crucial for achieving human-level robotic capabilities in manipulation tasks. As a promising solution, Vision-Based Tactile Sensors (VBTSs) offer high spatial resolution and...
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This is the paper with the most Huawei Fellow authors in the companyβs history
The core question it addresses is straightforward: How do you efficiently and cost-effectively build a training cluster for large-scale models that supports tens of thousands or even hundreds of thousands of AI chips?
The core question it addresses is straightforward: How do you efficiently and cost-effectively build a training cluster for large-scale models that supports tens of thousands or even hundreds of thousands of AI chips?
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DeepMind built an AI that replicates how a fruit fly walks, flies, and behaves β using MuJoCo, its open physics simulator
The work will help scientists understand what drives specific behaviors in the fly, finding links that labs can't always measure.
DeepMind applied this approach to multiple organisms β a virtual rodent, and now a fruit fly.
So what comes next for neuroscientists? The zebrafish β a widely studied creature which shares 70% of its protein-coding genes with humans.
GitHub
The work will help scientists understand what drives specific behaviors in the fly, finding links that labs can't always measure.
DeepMind applied this approach to multiple organisms β a virtual rodent, and now a fruit fly.
So what comes next for neuroscientists? The zebrafish β a widely studied creature which shares 70% of its protein-coding genes with humans.
GitHub
Nature
Whole-body physics simulation of fruit fly locomotion
Nature - A detailed whole-body model of the fruit fly, developed using a physics-based simulation and deep reinforcement learning, accurately replicates real fly behaviour.
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OpenAI now projects $125B in revenue in 2029, with $25B of that from new products not yet announced
The Information reports OpenAI forecasts revenue reaching $125 billion in 2029 and $174 billion in 2030, mainly from AI agents, subscriptions, monetizing free users, and potentially affiliate fees.
According to internal documents seen by The Information, OpenAI expects revenue in 2029 to include $29 billion from AI agents, $50 billion from ChatGPT subscriptions, $22 billion from API access, and $25 billion from monetizing free users and other new, unspecified products.
CEO Sam Altman mentioned recently affiliate fees or taking a percentage of sales generated through user searches as possible revenue sources, while CFO Sarah Friar told the Financial Times there are βno active plansβ for selling traditional advertising.
If they hit it, the current valuation ($300B) will be a steal; Google does ~$400B in revenue and is worth $2T.
The Information reports OpenAI forecasts revenue reaching $125 billion in 2029 and $174 billion in 2030, mainly from AI agents, subscriptions, monetizing free users, and potentially affiliate fees.
According to internal documents seen by The Information, OpenAI expects revenue in 2029 to include $29 billion from AI agents, $50 billion from ChatGPT subscriptions, $22 billion from API access, and $25 billion from monetizing free users and other new, unspecified products.
CEO Sam Altman mentioned recently affiliate fees or taking a percentage of sales generated through user searches as possible revenue sources, while CFO Sarah Friar told the Financial Times there are βno active plansβ for selling traditional advertising.
If they hit it, the current valuation ($300B) will be a steal; Google does ~$400B in revenue and is worth $2T.
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Trends in AI Supercomputers
Epoch AI dropped a map of the worldβs 500+ AI supercomputers.
β’ Performance doubling every 9 months.
β’ Hardware cost & power use doubling every year.
β’ xAIβs Colossus already gulps 300 MW β equal to 250 k homes β and thatβs only 2025.
If the trendline holds, the 2030 front-runner will burn 9 GW, pack 2 M chips, and sport a $200 B price tag.
The U.S. owns 75 % of todayβs compute muscle while China trails at 15 %.
Epoch AI dropped a map of the worldβs 500+ AI supercomputers.
β’ Performance doubling every 9 months.
β’ Hardware cost & power use doubling every year.
β’ xAIβs Colossus already gulps 300 MW β equal to 250 k homes β and thatβs only 2025.
If the trendline holds, the 2030 front-runner will burn 9 GW, pack 2 M chips, and sport a $200 B price tag.
The U.S. owns 75 % of todayβs compute muscle while China trails at 15 %.
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MIT researchers have developed a "periodic table" for machine learning β a groundbreaking framework that maps the connections between 20+ classical ML algorithms.
By revealing how these methods relate and overlap, the table opens up new ways for scientists to hybridize techniques, improving existing models or even inventing entirely new ones.
As proof of concept, the team fused two distinct algorithms using this framework and created a novel image classification method β outperforming current state of the art models by 8%.
By revealing how these methods relate and overlap, the table opens up new ways for scientists to hybridize techniques, improving existing models or even inventing entirely new ones.
As proof of concept, the team fused two distinct algorithms using this framework and created a novel image classification method β outperforming current state of the art models by 8%.
Tech Xplore
'Periodic table of machine learning' framework unifies AI models to accelerate innovation
MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies from ...
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Itβs announcement about the new lightweight ChatGPT deep research model (powered by a version of o4-mini) and updated limits confusing
In the end, it's a combination of tasks using "standard" deep research plus additional tasks using the lightweight version:
- Free - 5 tasks/month using the lightweight version
- Plus & Team - 10 tasks/month, plus an additional 15 tasks/month using the lightweight version
- Pro - 125 tasks/month, plus an additional 125 tasks/month using the lightweight version
- Enterprise - 10 tasks/month
In the end, it's a combination of tasks using "standard" deep research plus additional tasks using the lightweight version:
- Free - 5 tasks/month using the lightweight version
- Plus & Team - 10 tasks/month, plus an additional 15 tasks/month using the lightweight version
- Pro - 125 tasks/month, plus an additional 125 tasks/month using the lightweight version
- Enterprise - 10 tasks/month
OpenAI
Introducing deep research
An agent that uses reasoning to synthesize large amounts of online information and complete multi-step research tasks for you. Available to Pro users today, Plus and Team next.
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Liquid AI introduced architecture called Hyena Edge, a convolution-based multi-hybrid model that not only matches but outperforms strong Transformer-based baselines in computational efficiency and model quality on edge hardware, benchmarked on the Samsung S24 Ultra smartphone.
To design Hyena Edge, researchers used end-to-end automated model design framework βSTAR.
To design Hyena Edge, researchers used end-to-end automated model design framework βSTAR.
www.liquid.ai
Convolutional Multi-Hybrids for Edge Devices | Liquid AI
Today, we introduce a Liquid architecture called Hyena Edge, a convolution-based multi-hybrid model that not only matches but outperforms strong Transformer-based baselines in computational efficiency and model quality on edge hardware, benchmarked on theβ¦
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Why Do Multi-Agent LLM Systems Fail? Despite the growing excitement around Multi-Agent Systems (MAS), they often struggle to outperform single-agent approaches.
Berkeleyβs researchers analyzed 7 popular MAS frameworks across 200+ tasks, identifying 14 failure modes that hinder their effectiveness.
Paper.
Code.
Berkeleyβs researchers analyzed 7 popular MAS frameworks across 200+ tasks, identifying 14 failure modes that hinder their effectiveness.
Paper.
Code.
Google
MAST
In a Nutshell
Despite the increasing adoption of Multi-Agent Systems (MAS) , their performance gains often remain minimal compared to single-agent frameworks. Why do MAS fail?
We have conducted a systematic evaluation of MASs execution traces using Groundedβ¦
Despite the increasing adoption of Multi-Agent Systems (MAS) , their performance gains often remain minimal compared to single-agent frameworks. Why do MAS fail?
We have conducted a systematic evaluation of MASs execution traces using Groundedβ¦
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Stripe is building a NEW stablecoin product, powered by Bridge
If your company is:
- Based outside of the US, EU, or UK
- Interested in dollar access
Send a quick note about your company to [email protected]
If your company is:
- Based outside of the US, EU, or UK
- Interested in dollar access
Send a quick note about your company to [email protected]
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Perplexity released an agentic Voice Assistant
It uses web browsing and multi-app actions to book reservations, send emails and calendar invites, play podcasts/videos, and more
Currently available in the Perplexity app, but only on iOS
It uses web browsing and multi-app actions to book reservations, send emails and calendar invites, play podcasts/videos, and more
Currently available in the Perplexity app, but only on iOS