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Scooped by
Tony Shan
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Consider the GPU. An island of SIMD greatness that makes light work of matrix math. Originally designed to rapidly paint dots on a computer monitor, it was then found to be quite useful in large numbers by HPC practitioners. Enter GenAI, and now these little matrix mavens are in huge demand, so much so that we call it the GPU Squeeze.
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Tony Shan
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Today, the use of AI for image classification tasks has become ubiquitous. Millions of images are processed daily with increasing quality standards. However, beyond the quality of classification, optimizing other aspects such as model speed is crucial. Here, we delve into the proper optimization techniques for high-performance ML image preprocessing, focusing on 5 key methods.
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There is much ado these days regarding the language facility popular AI tools such as ChatGPT, Midjourney, Microsoft Copilot, and Gemini Connected appear to display. What do these systems comprehend? Do they understand? Are the underlying architectures a big leap toward artificial general intelligence (AGI) or an entertaining dead end? This article is not about that. This is a loosely related thread on how the language we use to describe AI systems affects our ability to govern them effectively.
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A new survey of C-suite executives and AI leaders shows while enterprise decision-makers trust the potential of AI, many lack confidence in their company’s strategy to execute as well as the data readiness to ensure reliability of AI outputs. Moreover, 7 in 10 executives say their AI strategy is not fully aligned to their business strategy today.
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According to the World Health Organization, 280 million people suffer from depression worldwide. More than half of those people aren’t diagnosed or treated because of the cost of care and effort involved in pursuing treatment. Fitness trackers can play a role in screening for depression and anxiety.
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Tony Shan
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Increasingly stringent privacy regulations—for example, GDPR (General Data Protection Regulation) in the European Union; and CCPA (California Consumer Privacy Act)—and sophisticated attacks leading to massive breaches have increased the demand for protecting data in use, or encryption in use. The encryption-in-use paradigm is important for security because encryption at rest protects that data only when it is in storage and encryption in transit protects the data only when it is being communicated over the network. In both cases, however, the data is exposed during computation—namely, while it is being used/processed at the servers. That processing window is the time when many data breaches happen, either at the hands of hackers or insider attackers.
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Tony Shan
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With organizations of all sorts facing increased urgency and unpredictability, being able to ask smart questions has become key. But unlike lawyers, doctors, and psychologists, business professionals are not formally trained on what kinds of questions to ask when approaching a problem. They must learn as they go. In their research and consulting, the authors have seen that certain kinds of questions have gained resonance across the business world. In a three-year project they asked executives to brainstorm about the decisions they’ve faced and the kinds of inquiry they’ve pursued. In this article they share what they’ve learned and offer a practical framework for the five types of questions to ask during strategic decision-making: investigative, speculative, productive, interpretive, and subjective. By attending to each, leaders and teams can become more likely to cover all the areas that need to be explored, and they’ll surface information and options they might otherwise have missed.
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Synthetic data is a class of data artificially generated through advanced methods like machine learning that can be used when real-world data is unavailable. It offers a multitude of compelling advantages, such as its flexibility and control, which allows engineers to model a wide range of scenarios that might not be possible with production data.
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Tony Shan
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This three-part series provides an inside look at the generative AI inside Microsoft Teams, Zoom, Cisco Webex, and Google Meet. Part 1 delivers a short discussion of how generative AI works and how LLMs are trained.
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Remote.It's new Scripting API solution leverages GraphQL to empower the overseeing and enhancing an extensive range of devices, including IoT devices deployed in incredibly diverse environments.
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Tony Shan
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SEATTLE – June 3rd, 2024 – Today, data storage and management company Qumulo said it achieved the industry’s fastest and most cost-effective cloud-native storage solution, as demonstrated by the latest SPECstorage Solution 2020 AI_IMAGE Benchmark results. Qumulo’s Azure Native Qumulo (ANQ) achieved an Overall Response Time (ORT) of 0.84ms with a total customer cost of just $400 for a five-hour burst period.
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Mistral AI, one of Europe’s premier artificial intelligence startups, has marked its entry into the programming and development space with the launch of Codestral, an open-weight generative AI model explicitly designed for code generation tasks.
Trained on a dataset of 80 programming languages, Codestral is designed for various coding functions and can complete any partial code using a fill-in-the-middle mechanism, according to a blog post released by Mistral. Developers can also use the model as a learning tool to improve their coding skills and minimize errors.
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Tony Shan
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Large Language Models (LLMs) can do astonishing things, like summarize complex data or generate creative content in seconds. Unfortunately, they also make things up— euphemistically referred to as hallucinating.
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Tony Shan
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Internal politics, organizational culture, and funding issues top the list of issues derailing CTOs’ change agenda — so too does demonstrating the value of innovation.
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Tony Shan
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Augmented by automation and self-healing capabilities, the use of container-based technology will also be key to not just deploying but also optimizing AI workloads at the edge.
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Tony Shan
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Tony Shan
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