Meta AI Open Sources GCM for Better GPU Cluster Monitoring to Ensure High Performance AI Training and Hardware Reliability
While the tech folks obsesses over the latest Llama checkpoints, a much grittier battle is being fought in the basements of data centers. As AI models scale to trillions of parameters, the clusters required to train them have become some of the most complex—and fragile—machines on the planet. Meta A...
Closing the Gap Between Text and Speech Understanding in LLMs
Large Language Models (LLMs) can be adapted to extend their text capabilities to speech inputs. However, these speech-adapted LLMs consistently underperform their text-based counterparts—and even cascaded pipelines—on language understanding tasks. We term this shortfall the text-speech understanding...
Our latest threat report examines how malicious actors combine AI models with websites and social platforms—and what it means for detection and defense.
A.R.I.S.: Automated Recycling Identification System for E-Waste Classification Using Deep Learning
Traditional electronic recycling processes suffer from significant resource loss due to inadequate material separation and identification capabilities, limiting material recovery. We present A.R.I.S. (Automated Recycling Identification System), a low-cost, portable sorter for shredded e-waste that a...
Constructive Circuit Amplification: Improving Math Reasoning in LLMs via Targeted Sub-Network Updates
Prior studies investigating the internal workings of LLMs have uncovered sparse subnetworks, often referred to as circuits, that are responsible for performing specific tasks. Additionally, it has been shown that model performance improvement through fine-tuning often results from the strengthening ...
Reusing Pre-Training Data at Test Time is a Compute Multiplier
Large language models learn from their vast pre-training corpora, gaining the ability to solve an ever increasing variety of tasks; yet although researchers work to improve these datasets, there is little effort to understand how efficient the pre-training apparatus is at extracting ideas and knowle...
A Coding Implementation to Simulate Practical Byzantine Fault Tolerance with Asyncio, Malicious Nodes, and Latency Analysis
In this tutorial, we implement an end-to-end Practical Byzantine Fault Tolerance (PBFT) simulator using asyncio. We model a realistic distributed network with asynchronous message passing, configurable delays, and Byzantine nodes that intentionally deviate from the protocol. By explicitly implementi...
Uber CEO Dara Khosrowshahi said the company’s employees have gone all in on AI, going so far as to build a chatbot of him that they use to practice their pitches.
Optimizing Token Generation in PyTorch Decoder Models
Hiding host-device synchronization via CUDA stream interleaving
The post Optimizing Token Generation in PyTorch Decoder Models appeared first on Towards Data Science.
Alibaba Qwen Team Releases Qwen 3.5 Medium Model Series: A Production Powerhouse Proving that Smaller AI Models are Smarter
The development of large language models (LLMs) has been defined by the pursuit of raw scale. While increasing parameter counts into the trillions initially drove performance gains, it also introduced significant infrastructure overhead and diminishing marginal utility. The release of the Qwen 3.5 M...
Vouched Launches Agent Checkpoint to Establish Trust in the Age of AI Agents
Agent Checkpoint brings transparency, security, and control to the new era of AI-to-AI commerce. Vouched, the leader in AI-powered identity verification, today announced Agent Checkpoint, a groundbreaking platform that helps organizations confidently engage in the next frontier of digital transforma...
OpenAI COO says ‘we have not yet really seen AI penetrate enterprise business processes’
Earlier this month, OpenAI launched a new platform called OpenAI Frontier for enterprises to build and manage agents, but OpenAI COO Brad Lightcap said that businesses haven’t yet seen AI adoption at scale. “One of the interesting things and some of the inspiration for the work we’ve been doing late...
Oneview Advances Intelligent Care Delivery with Ovie
Oneview Healthcare today announced the next evolution of Ovie, its digitally integrated Care Assistant designed to streamline nonclinical workflows and give care teams more uninterrupted time for clinical focus. Building on the voice assistant launched in 2025, the Ovie platform operates as an orche...
Authors: Junkai Xue | Sr Staff Software Engineer, Big Data Processing Platform; Zheyu Zha | Staff Software Engineer, Big Data Processing Platform; Jia Zhan | Principal Engineer, Online Systems; Alberto Ordonez Pereira | Sr Staff Software Engineer, Online SystemsOverviewA quota is an official limit o...
ABBYY Secures 22 New Patents, Pioneering the Future of Document AI
Building on the breakthroughs of 2024 and 2025, ABBYY is fueling a new era of AI-driven solutions in 2026 ABBYY today announced the issuance of 22 new patents in the past two years, reinforcing its position as a global leader in purpose-built AI for document process automation. Spanning innovations ...
A deep dive into the Sharpness-Aware-Minimization (SAM) algorithm and how it improves the generalizability of modern deep learning models
The post Optimizing Deep Learning Models with SAM appeared first on Towards Data Science.
Lag Features and Rolling Features in Feature Engineering
The success of machine learning pipelines depends on feature engineering as their essential foundation. The two strongest methods for handling time series data are lag features and rolling features, according to your advanced techniques. The ability to use these techniques will enhance your model pe...