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Perplexity AI announces a hybrid local-server inference orchestrator for Personal Computer, automatically routing AI tasks between on-device and cloud models.
The post Perplexity AI Introduces Hybrid Local-Server Inference Orchestrator for Personal Computer: Automatic On-Device and Cloud Task Routing appeared first on MarkTechPost.
SensorFM, a wearable health foundation model from Google Research, Google DeepMind, and university collaborators. We walk through its ViT-1D masked-autoencoder backbone, pretrained on more than one trillion minutes of unlabeled sensor signals from 5,000,000 consented participants. We examine the co-scaling results across four model sizes and four data volumes, including the case where capacity outruns data. We show how frozen embeddings plus a PCA-50 linear probe beat feature-engineered baselines on 34 of 35 tasks. We also review the agentic classroom that searched 30,516 prediction heads, and the clinician evaluation grounding a Personal Health Agent.
The post Google Research Introduces SensorFM: A Wearable Health Foundation Model Pretrained on One Trillion Minutes of Sensor Data appeared first on MarkTechPost.
Thinking Machines Lab published “The Future Worth Building Is Human.” The essay frames human participation, model ownership, and decentralized alignment as technical challenges. It ties them to interaction models and Tinker’s LoRA fine-tuning, where teams train and keep their own model weights.
The post Mira Murati’s Thinking Machines Lab Makes The Technical Case For Human-Centered AI Built On Customizable Model Weights appeared first on MarkTechPost.
Netflix engineers detailed how they handle wide partitions in Apache Cassandra for the TimeSeries Abstraction. Two approaches work together: Time Slice re-partitioning tunes future partitions at the table level, while dynamic partitioning detects and splits oversized partitions per TimeSeries ID on the read path. Detection runs via byte counting and Kafka, splits are checksum-validated, and Bloom filters route reads to parallel child partitions. Average read latency dropped from seconds to low double-digit milliseconds, with 500MB+ partitions staying available.
The post Netflix AI Team Cuts Wide-Partition Read Latency from Seconds to Milliseconds by Splitting Cassandra Partitions Per ID appeared first on MarkTechPost.
NVIDIA’s Nemotron 3 Ultra is a massive 550B open AI model that’s faster and smarter. We break it down in plain English for beginners
Moonshot AI Just Dropped a Coding Robot for Your Terminal 🚀 Imagine having a super-smart friend who lives inside your computer’s black command screen — the scary one most people avoid — and that friend can write, fix, and manage code for you. That’s basically what Moonshot AI has built with Kimi Code CLI. … Read more
NVIDIA Nemotron Just Dropped a Speech AI That Understands 40 Languages at Once — No, Really Imagine hiring a translator who speaks 40 languages, never needs a coffee break, and can write down everything you say while you are still saying it. That is basically what NVIDIA just built. Meet Nemotron 3.5 ASR — a … Read more
OpenAI’s GPT-5.6 family adds tiered models with max and ultra reasoning. Here is what early-level engineers should know.
The post OpenAI Previews GPT-5.6 With Sol, Terra, and Luna: Tiered Models, New Reasoning Modes, Limited Access appeared first on MarkTechPost.
DeepSeek open-sourced DSpark, a speculative decoding framework that attaches a draft module to existing DeepSeek-V4 weights. It pairs a parallel draft backbone with a lightweight Markov head to cut suffix decay, then adds confidence-scheduled verification that tailors how many tokens get checked to real-time GPU load. Offline, accepted length rises 16–31% over DFlash and Eagle3; in production it speeds per-user generation 57–85% over the MTP-1 baseline, losslessly. The training repo, DeepSpec, ships under MIT.
The post DeepSeek Releases DSpark, a Speculative Decoding Framework That Accelerates DeepSeek-V4 Per-User Generation 60–85% Over MTP-1 appeared first on MarkTechPost.
EverMind has open-sourced EverOS, a local-first memory runtime that stores AI agent memory as plain Markdown indexed by SQLite and LanceDB.