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Duro drags hardware product development into the age of agile

TechCrunch

To software developers, the process of creating a hardware product can seem distinctly 1980s. The new funding will be used to expand sales and marketing teams and to further develop Duro’s product lifecycle management (PLM) solutions. “To simplify things a little, the hardware industry is dominated by a bimodal culture.

Hardware 215
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Nvidia AI Enterprise adds generative AI microservices

CIO

of Nvidia’s enterprise-spanning AI software platform will feature a smorgasbord of microservices designed to speed app development and provide quick ways to ramp up deployments, the company announced today at its GPU Technology Conference. A host of further integrations is also coming to AI Enterprise 5.0, Version 5.0

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Intel spins off enterprise AI company Articul8 with outside funding

CIO

Intel has set up a new company, Articul8 AI, to sell enterprise generative AI software it developed. The system is already being used by enterprises including Scripps, Uptycs and Invest India. Enterprises will be able to deploy the Articul8 platform on premises, in the cloud, or in a hybrid deployment.

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EnCharge AI emerges from stealth with $21.7M to develop AI accelerator hardware

TechCrunch

EnCharge AI , a company building hardware to accelerate AI processing at the edge , today emerged from stealth with $21.7 Speaking to TechCrunch via email, co-founder and CEO Naveen Verma said that the proceeds will be put toward hardware and software development as well as supporting new customer engagements.

Hardware 216
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AllSpice thinks hardware developers lack their own ‘GitHub,’ so it is building one

TechCrunch

AllSpice , a collaborative hub designed for hardware development, came out of private beta on a mission to build a DevOps ecosystem inspired by GitHub. They bonded over frustrations at their respective jobs in what seemed like a hardware industry left behind to rely on PDFs and email to get things done versus software development.

Hardware 231
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Exafunction aims to reduce AI dev costs by abstracting away hardware

TechCrunch

But they share a common bottleneck: hardware. Developing systems on the bleeding edge often requires a huge amount of computing power. Further underlining the challenge, one source estimates that developing AI startup OpenAI’s language-generating GPT-3 system using a single GPU would’ve taken 355 years.

Hardware 243
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Is AI in the enterprise ready for primetime? Not yet.

CIO

There are a number of reasons why meaningful AI deployments within the enterprise will take longer than many imagine. AI hallucinations The problem of AI hallucinations, where a large language model (LLM) presents authentic-looking but made-up results, shouldn’t be underestimated for enterprise AI deployments.