The Hong Kong Stablecoin Ordinance will officially take effect on August 1 this year
The Hong Kong Monetary Authority will open the license application. It is expected that only a single digit number will be issued, but more than 40 companies are currently preparing to apply.
The applicants are basically the largest financial institutions and Internet companies in China.
The Hong Kong Monetary Authority will open the license application. It is expected that only a single digit number will be issued, but more than 40 companies are currently preparing to apply.
The applicants are basically the largest financial institutions and Internet companies in China.
OpenAI published "Working with 400,000 teachers to shape the future of AI in schools"
OpenAI joining the American Federation of Teachers as the founding partner to launch the National Academy for AI Instruction, a five-year initiative to equip 400,000 K-12 educators with OpenAI contributing $10 million over five years ($8 million in direct funding and $2 million in in-kind resources) alongside the United Federation of Teachers, Microsoft, and Anthropic in supporting the initiative
OpenAI joining the American Federation of Teachers as the founding partner to launch the National Academy for AI Instruction, a five-year initiative to equip 400,000 K-12 educators with OpenAI contributing $10 million over five years ($8 million in direct funding and $2 million in in-kind resources) alongside the United Federation of Teachers, Microsoft, and Anthropic in supporting the initiative
Openai
Working with 400,000 teachers to shape the future of AI in schools
OpenAI joins the American Federation of Teachers to launch the National Academy for AI Instruction.
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New Mistral Cookbook: Finetuning Pixtral on a satellite imagery dataset 🛰️
- How to call Mistral's batch inference API
- How to pass images (encoded in base64) in your API calls to Mistral's VLM (here Pixtral-12B)
- How to fine-tune Pixtral-12B on an image classification problem in order to improve its accuracy.
- How to call Mistral's batch inference API
- How to pass images (encoded in base64) in your API calls to Mistral's VLM (here Pixtral-12B)
- How to fine-tune Pixtral-12B on an image classification problem in order to improve its accuracy.
GitHub
cookbook/mistral/fine_tune/pixtral_finetune_on_satellite_data.ipynb at main · mistralai/cookbook
Contribute to mistralai/cookbook development by creating an account on GitHub.
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HuggingFace released SmolLM3: a strong, smol reasoner
> SoTA 3B model
> dual mode reasoning (think/no_think)
> long context, up to 128k
> multilingual: en, fr, es, de, it, pt
> fully open source (data, code, recipes)
> SoTA 3B model
> dual mode reasoning (think/no_think)
> long context, up to 128k
> multilingual: en, fr, es, de, it, pt
> fully open source (data, code, recipes)
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The biggest dataset of human written GPU Code all open-source? YES! GPU MODE have released around 40k human written code samples spanning Triton, Hip and PyTorch and it's all open. Train the new GPT to make GPTs faster.
huggingface.co
GPUMODE/kernelbot-data · Datasets at Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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Google DeepMind introduced T5Gemma: the next generation of encoder-decoder/T5 models
- Decoder models adapted to be encoder-decoder
- 32 models with different combinations
- Available in Hugging Face and Kaggle
- Decoder models adapted to be encoder-decoder
- 32 models with different combinations
- Available in Hugging Face and Kaggle
Googleblog
Google for Developers Blog - News about Web, Mobile, AI and Cloud
Explore T5Gemma – a new collection of encoder-decoder LLMs offering superior performance and efficiency – especially for tasks requiring deep input understanding, like summarization and translation, built on Gemma 2 models.
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xAI announced Grok 4
Here is everything you need to know:
Elon claims that Grok 4 is smarter than almost all grad students in all disciplines simultaneously. 100x more training than Grok 2. 10x more compute on RL than any of the models out there.
Performance on Humanity's Last Exam. Elon: "Grok 4 is post-grad level in everything!"
Scaling HLE - Training
More compute, higher intelligence.
(no tools).
With native tool calling, Grok 4 increases the performance significantly.
It's important to give AI the right tools. The scaling is clear.
Reliable signals are key to making RL work. There is still the challenge of data. Elon: "Ultimate reasoning test is AI operating in reality."
Scaling test-time compute. More than 50% of the text-only subset of the HLE problems are solved.
The curves keep getting more ridiculous.
Grok 4 is the single-agent version.
Grok 4 Heavy is the multi-agent version. Multi-agent systems are no joke.
Grok 4 uses all kinds of references like papers, reads PDFs, reasons about the details of the simulation, and what data to use.
Grok 4 Heavy performance is higher than Grok 4, but needs to be improved further. It's one of the weaknesses, according to the team.
Available as SuperGrok Heavy tier.
$30/m for Super Grok
$300/m for SuperGrok Heavy.
Voice updates included, too!
Grok feels snappier and is designed to be more natural.
- 2x faster
- 5 voices
- 10x daily user seconds.
Grok 4 models are available via the xAI API. 256K context window. Real-time data search.
Grok 4 for Gaming!
Video understanding is an area the team is improving, so it will get better.
What is next?
- Smart and fast will be the focus.
- Coding models are also a big focus.
- More capable multi-modal agents are coming too.
- Video generation models are also on the horizon.
Here is everything you need to know:
Elon claims that Grok 4 is smarter than almost all grad students in all disciplines simultaneously. 100x more training than Grok 2. 10x more compute on RL than any of the models out there.
Performance on Humanity's Last Exam. Elon: "Grok 4 is post-grad level in everything!"
Scaling HLE - Training
More compute, higher intelligence.
(no tools).
With native tool calling, Grok 4 increases the performance significantly.
It's important to give AI the right tools. The scaling is clear.
Reliable signals are key to making RL work. There is still the challenge of data. Elon: "Ultimate reasoning test is AI operating in reality."
Scaling test-time compute. More than 50% of the text-only subset of the HLE problems are solved.
The curves keep getting more ridiculous.
Grok 4 is the single-agent version.
Grok 4 Heavy is the multi-agent version. Multi-agent systems are no joke.
Grok 4 uses all kinds of references like papers, reads PDFs, reasons about the details of the simulation, and what data to use.
Grok 4 Heavy performance is higher than Grok 4, but needs to be improved further. It's one of the weaknesses, according to the team.
Available as SuperGrok Heavy tier.
$30/m for Super Grok
$300/m for SuperGrok Heavy.
Voice updates included, too!
Grok feels snappier and is designed to be more natural.
- 2x faster
- 5 voices
- 10x daily user seconds.
Grok 4 models are available via the xAI API. 256K context window. Real-time data search.
Grok 4 for Gaming!
Video understanding is an area the team is improving, so it will get better.
What is next?
- Smart and fast will be the focus.
- Coding models are also a big focus.
- More capable multi-modal agents are coming too.
- Video generation models are also on the horizon.
🔥4
Google introduced a new models for research & development of health applications:
1. MedGemma 27B Multimodal, for complex multimodal & longitudinal EHR interpretation
2. MedSigLIP, a lightweight image & text encoder for classification, search, & related tasks.
1. MedGemma 27B Multimodal, for complex multimodal & longitudinal EHR interpretation
2. MedSigLIP, a lightweight image & text encoder for classification, search, & related tasks.
research.google
MedGemma: Our most capable open models for health AI development
Salesforce introduced GTA1 – a new GUI Test-time Scaling Agent that is now #1 on the OSWorld leaderboard with a 45.2% success rate, outperforming OpenAI’s CUA o3 (42.9%).
Researchers introduced Foundation Model Self-Play
FMSPs combine the intelligence & code generation of foundation models with the curriculum of self-play & principles of open-endedness to explore diverse strategies in multi-agent games.
FMSPs combine the intelligence & code generation of foundation models with the curriculum of self-play & principles of open-endedness to explore diverse strategies in multi-agent games.
arXiv.org
Foundation Model Self-Play: Open-Ended Strategy Innovation via...
Multi-agent interactions have long fueled innovation, from natural predator-prey dynamics to the space race. Self-play (SP) algorithms try to harness these dynamics by pitting agents against...
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Now live: Full-Stack + Stripe on MiniMax Agent and more
1. Full-Stack + Stripe → Build monetizable apps in 1 sentence
2. PPTX Export → Better than top tools
3. Performance ↑ 30% faster, 23% leaner
4. Browser Agent → Now self-hosted, smarter & cheaper
1. Full-Stack + Stripe → Build monetizable apps in 1 sentence
2. PPTX Export → Better than top tools
3. Performance ↑ 30% faster, 23% leaner
4. Browser Agent → Now self-hosted, smarter & cheaper
agent.minimax.io
MiniMax Agent: Minimize Effort, Maximize Intelligence
Discover MiniMax Agent, your AI supercompanion, enhancing creativity and productivity with tools for meditation, podcast, coding, analysis, and more!
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China’s Kimi K2 is having its mini DeepSeek moment: Open-Source Agentic Model
1. 1T total / 32B active MoE model
2. SOTA on SWE Bench Verified, Tau2 & AceBench among open models
3. Strong in coding and agentic tasks
4. Multimodal & thought-mode not supported for now
With Kimi K2, advanced agentic intelligence is more open and accessible than ever.
API is here
- $0.15 / million input tokens (cache hit)
- $0.60 / million input tokens (cache miss)
- $2.50 / million output tokens
weights & code.
Our overall take:
- Performance between Claude 3.5 & Claude 4
- The UI generation seems great
- But the cost is only 20% of Claude 3.5
- So good enough for most coding agent with a lot more manageable cost.
Easiest way to use Kimi K2 in Claude Code:
- export ANTHROPIC_AUTH_TOKEN=YOUR_MOONSHOT_API
- export ANTHROPIC_BASE_URL=api.moonshot.ai/anthropic
- claude
1. 1T total / 32B active MoE model
2. SOTA on SWE Bench Verified, Tau2 & AceBench among open models
3. Strong in coding and agentic tasks
4. Multimodal & thought-mode not supported for now
With Kimi K2, advanced agentic intelligence is more open and accessible than ever.
API is here
- $0.15 / million input tokens (cache hit)
- $0.60 / million input tokens (cache miss)
- $2.50 / million output tokens
weights & code.
Our overall take:
- Performance between Claude 3.5 & Claude 4
- The UI generation seems great
- But the cost is only 20% of Claude 3.5
- So good enough for most coding agent with a lot more manageable cost.
Easiest way to use Kimi K2 in Claude Code:
- export ANTHROPIC_AUTH_TOKEN=YOUR_MOONSHOT_API
- export ANTHROPIC_BASE_URL=api.moonshot.ai/anthropic
- claude
moonshotai.github.io
Kimi K2: Open Agentic Intelligence
Kimi K2 is our latest Mixture-of-Experts model with 32 billion activated parameters and 1 trillion total parameters. It achieves state-of-the-art performance in frontier knowledge, math, and coding among non-thinking models.
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Nasdaq-listed Sonnet will merge with Rorschach I to form Hyperliquid Strategies, a crypto asset management firm expected to hold 12.6 million HYPE tokens and over $305 million in cash, with a valuation of approximately $888 million.
Backed by Paradigm and Galaxy Digital, HSI aims to list on Nasdaq later this year.
Backed by Paradigm and Galaxy Digital, HSI aims to list on Nasdaq later this year.
The Block
Nasdaq-listed Sonnet BioTherapeutics agrees to $888 million merger to become Hyperliquid Strategies, launch HYPE treasury
Hyperliquid Strategies is expected to hold 12.6 million HYPE tokens and $305 million in cash at closing of the deal.