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Know before you go: 6 lessons for enterprise GenAI adoption

CIO

That quote aptly describes what Dell Technologies and Intel are doing to help our enterprise customers quickly, effectively, and securely deploy generative AI and large language models (LLMs).Many That makes it impractical to train an LLM from scratch. In other words, we are walking a mile in our customers’ shoes.

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Should you build or buy generative AI?

CIO

Whether it’s text, images, video or, more likely, a combination of multiple models and services, taking advantage of generative AI is a ‘when, not if’ question for organizations. But many organizations are limiting use of public tools while they set policies to source and use generative AI models.

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Foxglove raises $15M to build dev infrastructure for robots

TechCrunch

While at Cruise, Macneil says that he saw firsthand the lack of off-the-shelf tooling for robotics and autonomous vehicle development; Cruise had to hire entire teams to build tooling in-house, including apps for visualization, data management, AI and machine learning, simulation and more. Image Credits: Foxglove.

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FPGA startup Rapid Silicon lands $15M to bring its first chip to market

TechCrunch

Field-programmable gate arrays (FPGA) , or integrated circuits sold off-the-shelf, are a hot topic in tech. Launched in 2021, the goal with Rapid Silicon is to promote, adopt and implement open source tech to address the low- to mid-range FPGA market, according to CEO and co-founder Naveed Sherwani.

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Your Generative AI strategy could use a startup’s touch

CIO

Use the learnings to avoid making similar missteps with GenAI. You might choose to bring the AI to your data by running an off-the-shelf or open-source solution in your corporate datacenter, ideally reducing complexity and risk. Accordingly, many organizations plan to boost GenAI funding, the survey found.

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Predibase exits stealth with a low-code platform for building AI models

TechCrunch

-based companies, 44% said that they’ve not hired enough, were too siloed off to be effective and haven’t been given clear roles. “The major challenges we see today in the industry are that machine learning projects tend to have elongated time-to-value and very low access across an organization.

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Why Reinvent the Wheel? The Challenges of DIY Open Source Analytics Platforms

Cloudera

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).