Artificial intelligence startup Baseten Labs Inc. today announced that it has closed a $150 million late-stage investment at a $2.15 billion valuation. BOND led the Series D round, which comes about six months after the company’s previous raise. It was joined by Alphabet Inc.’s CapitalG fund, Conviction, Premji Invest, 01A, IVP, Spark, Greylock and Scribble […] The post AI inference startup Baseten closes $150M investment backed by CapitalG appeared first on SiliconANGLE.| SiliconANGLE
From AI assistants doing deep research to autonomous vehicles making split-second navigation decisions, AI adoption is exploding across industries. Behind every one of those interactions is inference — the stage after training where an AI model processes inputs and produces outputs in real time. Today’s most advanced AI reasoning models — capable of multistep logic Read Article| NVIDIA Blog
Measures of Central Tendency For symmetric normal-like distributions there is a clear winner for measuring central tendency: the sample mean. The mean has the highest precision/efficiency and is also representative of a typical observation from the population distribution. The mean is not robust, e.g., is too affected by extreme values, when the distribution is heavy-tailed or asymmetric. For general continuous distributions with arbitrarily heavy tails or skewness, the sample median is robus...| Statistical Thinking
Event: ACTStats 2025 Annual Meeting Keynote Talk, Nashville TN USA Slides Details| Statistical Thinking
The development pace in the local LLM scene is relentless, and the team behind llama.cpp has rolled out another interesting update: a new high-throughput mode. The key claim is that by changing how the KV cache is handled for multiple, parallel requests, we can see significant performance gains. As a hands-on enthusiast, I wanted to […]| Hardware Corner
In a significant development for the AI community, the Qwen team has announced the release of its most powerful open agentic code model to date, the Qwen3-Coder-480B-A35B-Instruct.| Hardware Corner
The world of AI inference on Kubernetes presents unique challenges that traditional traffic-routing architectures weren’t designed to handle. While Istio has long excelled at managing microservice traffic with sophisticated load balancing, security, and observability features, the demands of Large Language Model (LLM) workloads require specialized functionality. That’s why we’re excited to announce Istio’s support for the Gateway API Inference Extension, bringing intelligent, model-aw...| Istio Blog
SemiAnalysis is hiring an analyst in New York City for Core Research, our world class research product for the finance industry. Please apply here It’s been a bit over 150 days since the launch of the Chinese LLM DeepSeek R1 shook stock markets and the Western AI world. R1 was the first model to be publicly […]| SemiAnalysis
The blueprint provides telcos with a recipe for building autonomous networks to drive significant improvements in network performance and efficiency with an agentic AI-based framework.| NVIDIA Blog
L’Oréal, LVMH and Nestlé use NVIDIA-accelerated agentic and physical AI to boost operational efficiency from product design to logistics.| NVIDIA Blog
Validated design for AI factories pairs accelerated infrastructure with NVIDIA software to streamline full-stack AI development for nations and enterprises.| NVIDIA Blog
The buying process begins when a prospect or a referral source considers you for a new engagement, or when a client considers you for a repeat performance. In this article, Rod Burkert reflects on this aspect of the engagement process.| QuickRead | News for the Financial Consulting Professional
GMKtec has officially priced its EVO-X2 SFF/Mini-PC at ~$2,000, positioning it as a potential option for AI enthusiasts looking to run large language models (LLMs) at home.| Hardware Corner
Overview Maximum likelihood estimation (MLE) is a gold standard estimation procedure in non-Bayesian statistics, and the likelihood function is central to Bayesian statistics (even though it is not maximized in the Bayesian paradigm). MLE may be unpenalized (the standard approach) or various penalty functions such as L1 (lasso, absolute value penalty), and L2 (ridge regression; quadratic) penalties may be added to the log-likelihood to achieve shrinkage (aka regularization). I have been doing...| Statistical Thinking
What follows are my notes on chapter 9 of Chip Huyen’s ‘AI Engineering’ book. This chapter was on optimising your inference and I learned a lot while reading it! There are interesting techniques like prompt caching and architectural considerations that I was vaguely aware of but hadn’t fully appreciated how they might work in real inference systems. Chapter 9: Overview Machine learning inference optimization operates across three fundamental domains: model optimization, hardware optim...| Alex Strick van Linschoten
Janice Pogue Lecture in Biostatistics, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada 2024-12-06 Slides| Statistical Thinking
Background Consider these four conditions: There is no reliable prior information about an effect and an uninformative prior is used in the Bayesian analysis There is only one look at the data The look was pre-planned and not data-dependent A one-sided assessment is of interest, so that one-tailed p-values and Bayesian posterior probabilities are used, where is the effect parameter of interest (e.g., difference in means, log effect ratio) and means “conditional on” or “given”. One-Sid...| Statistical Thinking
Firefox 130 will introduce an experimental new capability to automatically generate alt-text for images using a fully private on-device AI model. The feature will be available as part of Firefox’s built-in PDF editor, and our end goal is to make it available in general browsing for users with screen readers. The post Experimenting with local alt text generation in Firefox Nightly appeared first on Mozilla Hacks - the Web developer blog.| Mozilla Hacks – the Web developer blog
Meta’s open large language model — optimized and downloadable as an NVIDIA NIM — powers digital health and life sciences workflows.| NVIDIA Blog
Background As explained here, the power for a group comparison can be greatly increased over that provided by a binary endpoint, with greater increase when an ordinal endpoint has several well-populated categories or has a great many categories, in which it becomes a standard continuous variable. When a randomized clinical trial (RCT) is undertaken and deaths can occur, there are disadvantages to excluding the death and analyzing responses only on survivors using death as a competing risk, wh...| Statistical Thinking
Background A binary endpoint in a clinical trial is a minimum-information endpoint that yields the lowest power for treatment comparisons. A time-to-event outcome, when only a minority of subjects suffer the event, has little power gain over a pure binary endpoint, since its power comes from the number of events (number of uncensored observations). The highest power endpoint would be from a continuous variable that is measured precisely and reflects the clinical outcome situation. An ordinal ...| Statistical Thinking
Background The log-rank test is a Mantel-Haenszel “observed - expected frequency” type of test that was derived in a slightly ad hoc way by Nathan Mantel in 1966 and named the logrank test by R Peto and J Peto in 1972. It was later formally derived as the rank test having optimal local power for a shift in the type I extreme value (Gumbel) distribution. This horizontal shift is equivalent to a vertical shift in survival distributions after log-log transforming them. This is identical to s...| Statistical Thinking
A Definition All statistical procedures have assumptions. Even the most simple response variable (Y) where the possible values are 0 and 1, when analyzed using the proportion that Y=1, assumes that Y is truly binary, every observation has the same probability that Y=1, and that observations are independent. Non-categorical Y have more assumptions. Even simple descriptive statistics have assumptions as described below. But what does it mean that an assumption is required for using a statistica...| Statistical Thinking
Background Consider the problem of comparing two treatments by doing squential analyses by avoiding putting too much faith into a fixed sample size design. As shown here the lowest expected sample size will result from looking at the developing data as often as possible in a Bayesian design. The Bayesian approach computes probabilities about unknowns, e.g., the treatment effect, and one can update the current evidence base as often as desired, knowing that the current information has made pre...| Statistical Thinking
We have released a new version of Colour - Checker Detection that implements a new machine learning inference method to detect colour rendition charts, specifically the ColorChecker Classic 24 from X-| Colour Science
Vulkan (compute) has the potential to be the next-generation GPGPU standard for various GPUs to support various domains; one immediate compelling application, is machine learning inference for resource-constrained scenarios like in mobile/edge devices and for gaming. This blog post explains the technical and business aspects behind and discusses the challenges and status.| Lei.Chat()
Unique challenges for edge/mobile ML inference, contrasting with training and inference in the cloud| Lei.Chat()
With Habana’s SynapseAI 1.8.0 release support of DeepSpeed Inference, users can run inference on large language models, including BLOOM 176B.| Habana Developers
We have optimized additional Large Language Models on Hugging Face using the Optimum Habana library.| Intel Gaudi Developers
Retrieval-augmented generation (RAG) is a technique for enhancing the accuracy and reliability of generative AI models with facts fetched from external sources.| NVIDIA Blog
Welcome to this tutorial on how to create a custom inference handler for Hugging Face Inference Endpoints.| www.philschmid.de