WiFi signals can accurately measure heart rate without the need for wearables, utilizing advanced algorithms to interpret signal variations caused by human movement.
Memory is slow, Disk is fast – Part 2
Sourcing data directly from disk can outperform memory caching due to the stagnation of memory access latency while disk bandwidth continues to grow, necessitating new approaches to leverage hardware advancements effectively.
Apertus 70B: Truly Open - Swiss LLM by ETH, EPFL and CSCS
Apertus-70B-2509 is a new addition to the Apertus LLM collection, showcasing advancements in large language models with enhanced capabilities.
Why ML Needs a New Programming Language
Mojo, a new programming language by Chris Lattner, aims to enhance GPU programming by combining ease of use with type-safe metaprogramming, allowing developers to harness the full power of modern hardware while maintaining productivity.
Using AI to perceive the universe in greater depth
Deep Loop Shaping enhances gravitational wave observatories by reducing noise and improving control, enabling astronomers to gather more detailed data on cosmic events like black hole mergers and neutron star collisions.
How big are our embeddings now and why?
Embedding sizes have significantly increased, with models like OpenAI's using 1536 dimensions, reflecting a shift from the previous standard of 300 dimensions due to advancements in training data and architecture.
Now Live: Europe’s First Exascale Supercomputer, JUPITER, Accelerates Climate Research, Neuroscience, Quantum Simulation
JUPITER, Europe’s first exascale supercomputer, is now operational, enabling unprecedented computational power for scientific research and AI applications.
Liquid Cooling Exhibits
Liquid cooling innovations showcased at Hot Chips 2025 emphasize microjet technology for optimized heat dissipation, allowing targeted cooling over chip hotspots rather than uniform distribution.
How to Build a High-Performance UR5 Inverse Kinematics Solver with IK-Geo
The UR5 Inverse Kinematics (IK) solver developed using IK-Geo is the fastest and most accurate in testing, achieving speeds over 40x faster than IKFast and errors near machine epsilon ((10^{-16})).
Fantastic Pretraining Optimizers and Where to Find Them
AdamW remains the leading optimizer in language model pretraining, yet a systematic study reveals that fair comparisons of optimizers require rigorous hyperparameter tuning and evaluations across various model scales and data-to-model ratios, as many claims of speedup are overstated.
[R] The Illusion of Progress: Re-evaluating Hallucination Detection in LLMs
Current benchmarks for hallucination detection in LLMs are inadequate, often yielding low-signal results that fail to address real-world high-stakes scenarios, as highlighted in the paper here.
[D] Intel discontinuing SGX forced us to rethink our confidential compute stack for private model training
Intel's discontinuation of SGX in 2025 has prompted a shift towards a multi-TEE approach, utilizing Phala Network to integrate Intel TDX, AMD SEV, and AWS Nitro under a unified API for enhanced confidential computing.
[P] I Was Wrong About Complex ML Solutions - Gower Distance Beat My UMAP Approach
Gower distance, a method for calculating distances in mixed categorical and numerical data, often outperforms complex ML solutions like UMAP, especially in small-to-medium datasets, highlighting the value of simplicity in machine learning.
[D] Performance overhead of running ML inference in hardware-isolated environments - production metrics
Performance overhead for ML inference in trusted execution environments (TEEs) is currently at 5-8%, significantly lower than the 30-40% reported in earlier studies, indicating improved efficiency in compliance-driven applications like fraud detection.
ArcMemo: Abstract Reasoning Composition with Lifelong LLM Memory
ArcMemo enhances LLM memory by transitioning from instance-based to concept-level memory, allowing for the reuse of modular abstractions from reasoning traces, thus improving reasoning capabilities across queries.