AI Pulse

Breaking the bottleneck: Why AI demands an SSD-first future

Breaking the bottleneck: Why AI demands an SSD-first future

As artificial intelligence (AI) adoption increases, data centers are experiencing challenges primarily related to storage, particularly with traditional hard disk drives (HDDs). Once used primarily for cold data storage, many datasets are now frequently accessed, necessitating low-latency and high-throughput storage systems that can manage intensive parallel computations. While HDDs are still viable for low-cost cold

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This new AI technique creates ‘digital twin’ consumers, and it could kill the traditional survey industry

This new AI technique creates ‘digital twin’ consumers, and it could kill the traditional survey industry

A recent research paper, released on October 9, outlines a new method enabling large language models (LLMs) to replicate human consumer behavior with notable accuracy. This innovation could potentially transform the market research industry, which is valued in the billions. The technique aims to generate synthetic consumer profiles capable of delivering not only realistic product

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Salesforce bets on AI 'agents' to fix what it calls a $7 billion problem in enterprise software

Salesforce bets on AI 'agents' to fix what it calls a $7 billion problem in enterprise software

Salesforce is hosting its Dreamforce conference this week, attracting around 50,000 attendees. During the event, the company unveiled Agentforce 360, a comprehensive overhaul of its product offerings aimed at fostering “agentic enterprises.” This concept refers to organizations where AI agents work in tandem with human employees, potentially handling up to 40% of tasks across various

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An earthling’s guide to planet hunting

An earthling’s guide to planet hunting

At her lab in a redwood forest, Jensen-Clem and her students are exploring new technologies to enhance the clarity of Keck Observatory’s primary honeycomb mirror and its smaller “deformable” mirror. These deformable mirrors can adjust their shape quickly based on real-time measurements from atmospheric sensors, allowing them to correct distortions caused by the Earth’s atmosphere.

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Here's what's slowing down your AI strategy — and how to fix it

Here's what's slowing down your AI strategy — and how to fix it

In many large companies, data science teams face significant delays in deploying advanced models due to bureaucratic processes. For instance, a data science team may spend six months developing a model that predicts customer churn with 90% accuracy, only to see it become inactive while awaiting approval from a risk review committee. This situation highlights

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