29 May

Prodigy | 0.58.0 | ZenML Documentation

stp2y0 CommentsNews
Annotating data using Prodigy.Prodigy is a modern annotation tool for creating training and evaluation data for machine learning models. You can also use Prodigy to help you inspect and clean your data, do error analysis and develop rule-based systems to use in combination with your statistical models.Prodigy is a paid annotation tool. You will need a Prodigy is a paid tool. A license is required to download and use it with ZenML.The Prodigy Python library includes a range of pre-built workflows and command-line commands for various tasks, and well-documented components for implementing your own workflow scripts. Your scripts can specify…
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IBM Storage Perpetual offers long-term upgrades, low cost – SiliconANGLE
29 May

IBM Storage Perpetual offers long-term upgrades, low cost – SiliconANGLE

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As the wave of artificial intelligence technology opens possibilities and constrains budgets, IBM Corp. is offering an IBM Storage Assurance Perpetual model, a price-protected subscription for businesses wanting modern storage without breaking the bank. “What’s really unique and awesome about this Perpetual model is that it’s on client-owned infrastructure … that’s what’s really exciting for clients here, is it’s assets that they own but still get that price protection flexibility on,” said Audrey O’Donnell (pictured), product manager of IBM FlashSystem at IBM Corp. IBM’s Audrey O’Donnell talks to theCUBE about new storage options and AI’s impact on company storage methods.…
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How to train your ViT for OOD Detection
29 May

How to train your ViT for OOD Detection

stp2y0 CommentsViral News
arXiv:2405.17447v1 Announce Type: new Abstract: VisionTransformers have been shown to be powerful out-of-distribution detectors for ImageNet-scale settings when finetuned from publicly available checkpoints, often outperforming other model types on popular benchmarks. In this work, we investigate the impact of both the pretraining and finetuning scheme on the performance of ViTs on this task by analyzing a large pool of models. We find that the exact type of pretraining has a strong impact on which method works well and on OOD detection performance in general. We further show that certain training schemes might only be effective for a specific type of…
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SambaNova breaks Llama 3 speed record with 1,000 tokens per second
29 May

SambaNova breaks Llama 3 speed record with 1,000 tokens per second

stp2y0 CommentsChat-GPT
Time's almost up! There's only one week left to request an invite to The AI Impact Tour on June 5th. Don't miss out on this incredible opportunity to explore various methods for auditing AI models. Find out how you can attend here. There is no one simple speedometer to measure the speed of a generative AI model, but one of the leading approaches is by measuring how many tokens per second a model handles. Today, SambaNova Systems announced that it has achieved a new milestone in terms of gen AI performance, hitting a whopping 1,000 tokens per second with the…
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Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attention
29 May

Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attention

stp2y0 CommentsViral News
arXiv:2405.16042v1 Announce Type: new Abstract: When reading temporarily ambiguous garden-path sentences, misinterpretations sometimes linger past the point of disambiguation. This phenomenon has traditionally been studied in psycholinguistic experiments using online measures such as reading times and offline measures such as comprehension questions. Here, we investigate the processing of garden-path sentences and the fate of lingering misinterpretations using four large language models (LLMs): GPT-2, LLaMA-2, Flan-T5, and RoBERTa. The overall goal is to evaluate whether humans and LLMs are aligned in their processing of garden-path sentences and in the lingering misinterpretations past the point of disambiguation, especially when extra-syntactic information (e.g.,…
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Samsung will stuff the Galaxy Watch with new AI health-tracking features
29 May

Samsung will stuff the Galaxy Watch with new AI health-tracking features

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Samsung will add new AI-based health and fitness features to the Galaxy Watch later this year. The company announced on-device AI features on Wednesday, including personalized health scores, tips, sleep indicators and suggested workout routines.One of the Galaxy Watch’s big AI upgrades is a new Energy Score, which learns from various personal metrics to provide “comprehensive health insights.” The model draws on a variety of sleep data, including when the wearer went to bed, how long and how well they slept and their heart's rate and variability during sleep. Physical activity during waking hours is also taken into account.Along similar…
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Elon Musk’s xAI secures $6B to challenge OpenAI in AI race
29 May

Elon Musk’s xAI secures $6B to challenge OpenAI in AI race

stp2y0 CommentsChat-GPT
Elon Musk founded xAI last summer, and The Verge just reported that it’s already making waves by announcing a massive $6 billion funding round. According to the company, this money will help bring xAI’s first products to market, build advanced infrastructure, and accelerate research and development efforts into future technologies. Musk has some history in the AI space. He co-founded OpenAI in 2015 alongside the current CEO, Sam Altman, and others. However, he parted ways with the company in 2018 due to disagreements over its priorities and direction, specifically OpenAI’s move away from open-source AI models and towards proprietary, closed models that they…
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Virtual Care Drives Rise In Addiction Treatment Startup Funding
29 May

Virtual Care Drives Rise In Addiction Treatment Startup Funding

stp2y0 CommentsRAG models
When Hollywood takes on addiction recovery, the script typically conjures up dingy rooms where the down-on-their-luck gather to share their struggles and fears. The prevailing venture-funded model, in contrast, offers little cinematic eye candy. Rather, the focus is mostly on startups where people in treatment message and video chat with care providers and use apps to track prescriptions. Visual appeal aside, there’s plentiful funding to bolster this smartphone-driven vision. Addiction-focused virtual care startups have pulled in hundreds of millions for business models largely based on building offerings scalable enough to meet the massive demand for treatment. Much of the funding…
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