Accelerate NLP inference with ONNX Runtime on AWS Graviton processors | Amazon Web Services

Accelerate NLP inference with ONNX Runtime on AWS Graviton processors | Amazon Web Services

ONNX is an open source machine learning (ML) framework that provides interoperability across a wide range of frameworks, operating systems, and hardware platforms. ONNX Runtime is the runtime engine used for model inference and training with ONNX. AWS Graviton3 processors are optimized for ML workloads, including support for bfloat16, Scalable Vector Extension (SVE), and Matrix Multiplication (MMLA) instructions. Bfloat16 accelerated SGEMM kernels and int8 MMLA accelerated Quantized GEMM (QGEMM) kernels in ONNX have improved inference performance by up to 65% for fp32 inference and up to 30% for int8 quantized inference for several natural language processing (NLP) models on AWS…
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Here’s how machine learning can violate your privacy

Here’s how machine learning can violate your privacy

Machine learning has pushed the boundaries in several fields, including personalized medicine, self-driving cars and customized advertisements. Research has shown, however, that these systems memorize aspects of the data they were trained with in order to learn patterns, which raises concerns for privacy. In statistics and machine learning, the goal is to learn from past data to make new predictions or inferences about future data. In order to achieve this goal, the statistician or machine learning expert selects a model to capture the suspected patterns in the data. A model applies a simplifying structure to the data, which makes it…
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Fullstory’s new platform enables harnessing customer behavioral data as a standalone source – SiliconANGLE

Fullstory’s new platform enables harnessing customer behavioral data as a standalone source – SiliconANGLE

Data analytics startup Fullstory Inc. says it wants to enhance the capabilities of artificial intelligence applications by providing them with the behavioral data they need to understand customer’s sentiments properly. To do this, it has announced a new platform called Data Direct, which automates the collection, synchronization and cleaning of structured, AI-ready behavioral data that can be fed into any application. By doing this, it says it can provide companies with more insightful web and mobile sentiment signals, allowing them to adapt the way they engage with customers and, hopefully, enable more positive interactions. Data Direct is said to transform…
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Doctor-designed food prescriptions could help patients cut medical costs for hypertension and cancer

Doctor-designed food prescriptions could help patients cut medical costs for hypertension and cancer

Doctors' custom food prescriptions featuring beans and greens are helping patients prevent illness.A doctor said healthy food plans can help address high healthcare costs and chronic illness rates.This article is part of "Trends in Healthcare," a series about the innovations and industry leaders shaping patient care. Thanks for signing up! Access your favorite topics in a personalized feed while you're on the go. download the app Picture this: At your next health checkup, your doctor hands you a prescription for potatoes instead of pills.For some patients, this scenario is becoming a reality.Providing personalized recommendations for healthy food — along with information…
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AI Chip Deficit: Alternatives to Nvidia GPUs – EE Times

AI Chip Deficit: Alternatives to Nvidia GPUs – EE Times

//php echo do_shortcode('[responsivevoice_button voice="US English Male" buttontext="Listen to Post"]') ?> In January 2024, leading private equity firm Blackstone announced it was building a $25 billion AI data empire. A few months later, OpenAI and Microsoft followed suit with a proposition to build Stargate, a $100 billion AI supercomputer that will launch the company to the forefront of the AI revolution.   Of course, this is not a surprise. With the rapid acceleration the AI sector has witnessed over the past few years, industry giants all over the world are in a frantic haste to get front-row seats. Experts already predict the…
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Will AI transform law?

Will AI transform law?

A year ago, the startup DoNotPay claimed to have built a “robot lawyer” capable of arguing cases before the Supreme Court. There is no evidence that such a technology exists, and attempts to use AI write arguments have ended badly. But DoNotPay’s marketing gimmick was successful in getting wide attention, which goes to show that in the era of large language models, the idea of AI replacing lawyers seems quite plausible to many people.As we’ve written before, we think such expectations are extremely premature, and we shouldn’t read much into ChatGPT’s performance in simulated scenarios such as the bar exam.…
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From Constant Firefighting to Innovation: How Databricks’s Money Team Halved Their Ops Burden in One Year!

From Constant Firefighting to Innovation: How Databricks’s Money Team Halved Their Ops Burden in One Year!

In the last year, the Databricks Money Engineering Team has embarked on an exhilarating journey, achieving nearly double our operational efficiency. We are excited to share this transformative experience with you, highlighting the specific strategies that fueled our success. In this post, we will discuss how introducing an Ops Czar reduced operational burden while at the same time empowered our engineering team. We will discuss pragmatism and Databricks first principles."In Unity, Strength": How Collective Effort and Strategic Efficiency Doubled Our CapabilitiesThe Money team is at the heart of commercializing Databricks's products, such as Workflows and Notebooks. We handle everything from…
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Automatic retry function with Kotlin flows

Automatic retry function with Kotlin flows

Table of contents Short code example Why use this? My app on the Google play store Resources Programming Android with Kotlin: Achieving Structured Concurrency with Coroutines. Chapter 10 Short code example Here is the code that will allow you to make automatic retries on a flow: fun <T, R : Any> Flow<T>.mapWithRetry( action: suspend (T) -> R, predicate: suspend (R, attempt: Int) -> Boolean ) = map { data -> var attempt = 0L var shallRetry: Boolean var lastValue: R? = null do { val tr = action(data) shallRetry = predicate(tr, (++attempt).toInt()) if (!shallRetry) lastValue = tr } while (shallRetry)…
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