IBM researchers, together with ETH Zürich, have unveiled a new class of Analog Foundation Models (AFMs) The aim of this project is to provide a bridge between the large language models and Analog In Memory Computing hardware. AIMC has long promised a radical leap in efficiency—running models with a billion parameters in a footprint small enough for embedded or edge devices—thanks to dense non-volatile memory (NVM) that combines storage and computation. The Achilles heel of the technology has always been noise. Matrix-vector multiplications performed directly within NVM devices result in non-deterministic error that can cripple commercial models. Why is analog…
Auteur: Gavin Wallace
Coral Protocol released Coral v1 The company is standardizing the way developers create agents. Learn, create, and perform Agents AI across heterogeneous platforms. This release focuses on an Runtime based on MCP This is the (Coral Server). Agent-to-agent threaded messaging with mentionsA developer’s workflow (CLI+Studio) for Orchestration and observabilityThe aforementioned is accompanied by the. Public registry For agent discovery. Coral is planning to Solana offers pay-per use payouts “coming soon,” This service is not available to all. What Coral v1 Actually Ships The first time, anyone can: → Publish AI agents on a marketplace where the world can discover them…
What exactly is being measured when a judge LLM assigns a 1–5 (or pairwise) score? You can find out more about this by clicking here. “correctness/faithfulness/completeness” The rubrics used are specific to a project. If a score is not based on task definitions, it can become distorted by the business outcome (e.g. “useful marketing post” vs. “high completeness”). Surveys of LLM-as-a-judge (LAJ) note that rubric ambiguity and prompt template choices materially shift scores and human correlations. What is the stability of judge decisions regarding prompt positioning and formatting? More controlled large studies found position biasThe order in which identical candidates…
One thing is that the data processing systems are relatively slow compared with those found on Earth. The systems would constantly be bombarded with radiation. “obsolescence would be a problem” Because repairs and upgrades are incredibly difficult. Hajimiri is convinced that data centres in space will be an option someday but is hesitant to give a date. “Definitely it would be doable in a few years,” “He said” “The question is how effective they would be, and how cost-effective they would become.”It isn’t just the rudimentary thoughts of technologists or academics who are mulling over the idea. Some elected officials…
This tutorial explores how to run MATLAB code in Python using the oct2py libraries. The environment is set up on Google Colab. We exchange data with NumPy/Octave, call and write.m files and visualize plots produced in Octave using Python. This allows us to take advantage of the Python ecosystem, while still leveraging the numerical and syntax power of MATLAB/Octave. See the FULL CODES here. !apt-get -qq update !apt-get -qq install -y octave gnuplot octave-signal octave-control > /dev/null Install oct2py, scipy, matplotlib and pillow with!python. From oct2py: import Oct2Py. Oct2PyError Import numpy, matplotlib.pyplot and textwrap as the appropriate nps. Import savemat and…
YouTube’s annual Made on YouTube conference this week unveiled a plethora of updates, tools, and features aimed at creators. These included updates to YouTube Live and new ways to monetize. Updates on Studio include “likeness” The company offers new AI tools to podcasters for promoting their shows. All the latest news from Made on YouTube Studio A is a new studio YouTube CEO Neal Mohan speaks at Made on YouTube in 2025Image credits:You can watch videos on YouTube A company displayed its best. new and updated tools to StudioCreators can use it to track their analytics and manage their channels.…
Original version You can also find out more about the following: this story The following appeared: Quanta Magazine.Chinese AI firm DeepSeek launched a chatbot called R1 earlier this year, which attracted a lot of attention. It’s mostly a chatbot focused on the fact The stock prices of many Western tech companies plummeted as a result. Nvidia, which sells the chips that run leading AI models, was among the worst hit. The stocks of Western technology companies plunged as a result. Nvidia sells chips used to run the leading AI models. lost more stock value in a single day More than…
xAI is a new technology introduced Grok-4-FastGrok-4 is a successor designed to be cost-effective that merges “reasoning” You can also find out more about the following: “non-reasoning” The system can control weights by prompting users. The model targets high-throughput search, coding, and Q&A with a 2M-token context window Use native tools-use RL to decide when you want to surf the internet, run code or use tools. Architecture note Grok Previous releases split in long-chain “reasoning” Shorten it to “non-reasoning” Different models have different responses. Grok-4-Fast’s Unified weight space Reduces latency from end to end and the tokens used by guiding…
Xiaomi MiMo’s MiMo Team released MiMo Audio. This 7-billion parameter audio-language system runs an interleaved speech model and text over discretized voice, scaling up pretraining past 100 million hours. What is actually new?? MiMo-Audio relies on a custom RVQ tokenizer to achieve both high-quality reconstruction and semantic fidelity. The tokenizer runs at 25 Hz and outputs 8 RVQ layers (≈200 tokens/s), giving the LM access to “lossless” It can also model text and speech auto-regressively. Architecture: patch encoder → 7B LLM → patch decoder To handle the audio/text rate mismatch, the system packs four timesteps per patch for LM consumption…
MIT researchers (Han Lab) introduced LEGOThe a compiler-like A framework for automatically converting tensor workloads into a graphical interface (e.g. GEMM Conv2D Attention MTTKRP). RTL synthesizable is generated for spatial accelerators—no handwritten templates. The front-end of LEGO expresses dataflows and workloads using a Relational affine representationBuilds Interconnects for FU (functional units) The following are some examples of how to get started: Memory on a chip Layouts and Supports Fusing spatial dataflows in a single design. Back end is a primitive graph. linear programming Use graph transformations to add pipeline registers, rewire transmissions, or extract reduction trees. Reduce area and Power.…