Author: Advanced AI Bot

IBM Corp. said today it’s buying the database company DataStax Inc. in an effort to turbocharge the capabilities of its growing watsonx portfolio of artificial intelligence development tools. The company said it’s planning to integrate DataStax’s technology into watsonx’s generative AI products, where it will help manage and streamline access to the vast amounts of data they require. In addition, the deal will enhance its commitment to building open-source AI products. The financial terms of the deal were not disclosed. It’s expected to close sometime during the second quarter, subject to regulatory approval. DataStax’s flagship product is a cloud-based database-as-a-service…

Security engineer was the most common title in cybersecurity job listings in 2024, according to security and IT workforce management platform provider CyberSN. Its report “U.S. Cybersecurity Job Posting Data” was created by pulling together job postings from 30 major job boards and Fortune 500 companies’ job boards between January 2022 and December 2024. The report shows which roles are growing, which are decreasing in demand, and other hiring trends. Security engineer and security analyst job-seekers have a lot of options The top 10 most in-demand roles posted in 2024 were: Security engineer (64,300 posted jobs) Security analyst (45,496 posted…

OpenAI is reportedly nearing a massive $40 billion funding round led by Japan’s SoftBank Group, according to Bloomberg. The investment could make SoftBank the largest backer of the ChatGPT creator after Microsoft. The round also includes participation from Magnetar Capital, Coatue Management, and Altimeter Capital. Bloomberg noted SoftBank may contribute up to $25 billion, reflecting CEO Masayoshi Son’s bold strategy to dominate the artificial intelligence landscape. This comes on the heels of a $500 billion joint initiative between SoftBank and OpenAI—dubbed Project Stargate—aimed at building expansive AI infrastructure in the U.S., including data centers to boost OpenAI’s computing capabilities. Increased…

From clinical operations to drug development, we mapped 85+ startups bringing generative AI to the healthcare and life sciences industries. Healthcare and life sciences companies are turning to generative AI to address 2 critical challenges: soaring costs and staffing shortages. Estimates indicate that US hospitals lose $262B annually to revenue cycle inefficiencies, while drugmakers spend more than $1B on average to develop a single drug. Meanwhile, the healthcare workforce in the US faces high burnout and a projected shortage of 124,000 physicians by 2034, according to the Association of American Medical Colleges. Generative AI solutions are addressing these concerns by…

Nine companies joined The Crunchbase Unicorn Board in February with healthcare and cybersecurity the leading sectors for new unicorn companies. While by itself it wasn’t the leading sector for unicorn creation last month, artificial intelligence was a significant technology in the new healthcare and cybersecurity sector unicorns, as well as for those companies in the sales and marketing industries. Four of the new February unicorns are U.S.-based, and Saudi Arabia, China, Israel, Ireland and Canada each added one new unicorn last month. Private equity continues to play an outsized role in private venture-backed companies. Of the nine new unicorns, growth…

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Last August, the National Institute of Standards and Technology (NIST) released the first three “post-quantum encryption standards” designed to withstand an attack from a quantum computer. For years, cryptography experts have worried that the advent of quantum computing could spell doom for traditional encryption methods. With the technology now firmly on the horizon, the new NIST standards represent the first meaningful step toward post-quantum protections.  But is quantum computing the threat to encryption it’s been made out to be? While it’s…

AI models are being cranked out at a dizzying pace, by everyone from Big Tech companies like Google to startups like OpenAI and Anthropic. Keeping track of the latest ones can be overwhelming.  Adding to the confusion is that AI models are often promoted based on industry benchmarks. But these technical metrics often reveal little about how real people and companies actually use them.  To cut through the noise, TechCrunch has compiled an overview of the most advanced AI models released since 2024, with details on how to use them and what they’re best for. We’ll keep this list updated…

This paper posits the interesting question: How much of the performance of Mamba, S4, and other state-space-like models is actually just attributable to some very core concepts – rather than their elaborate architectures. The authors construct minimal versions of GRUs and LSTMs and report competitive performance. Paper: Abstract: The scalability limitations of Transformers regarding sequence length have renewed interest in recurrent sequence models that are parallelizable during training. As a result, many novel recurrent architectures, such as S4, Mamba, and Aaren, have been proposed that achieve comparable performance. In this work, we revisit traditional recurrent neural networks (RNNs) from over…

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