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TechCrunch+ roundup: Technical due diligence, web3’s promise, how to hire well

TechCrunch

One of my favorite examples is in the first Harry Potter movie, when Hagrid takes Harry to Diagon Alley, the magical shopping district that introduces him (and us) to the world of wizarding. 8 questions to answer before your startup faces technical due diligence. Tomorrow, we’ll run his detailed TDD checklist.

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What is SAFe? A framework for scaling business agility

CIO

Key elements of SAFe: Value streams and agile release trains At the core of any successful SAFe implementation are value streams and agile release trains (ARTs). The third level, Large Solution Level, involves two or more ARTs coordinated as a solution train. Apply systems thinking into all facets of development.

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Google expands program to help train the formerly incarcerated

TechCrunch

Last April, Google launched Grow with Google Career Readiness for Reentry, a program created in partnership with nonprofits to offer job readiness and digital skills training for formerly incarcerated individuals. For example, U.S. ” Meanwhile, Google.org, Google’s charitable arm, will provide $4.25 ”

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4 hidden risks of your enterprise cloud strategy

CIO

And those massive platforms sharply limit how far they will allow one enterprise’s IT due diligence to go. When performing whatever minimal due diligence the cloud platform permits — SOC reports, GDPR compliance, PCI ROC, etc. When Blauner worked at Citi, for example, that MVP was international funds transfers. “If

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Sesamm bags $37M to give corporates ESG insights using natural language processing

TechCrunch

Companies can access Sesamm’s flagship product, TextReveal , via several conduits, including an API that brings Sesamm’s NLP engine into their own systems. Elsewhere, private equity firms can use Sesamm for due diligence on potential acquisition or investment targets.

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When your AI chatbots mess up

CIO

But as the numbers of new gen AI-powered chatbots grow, so do the risks of their occasional glitches—nonsensical or inaccurate outputs or answers that are not easily screened out of the large language models (LLMs) that the tools are trained on. Hallucinations occur when the data being used to train LLMs is of poor quality or incomplete.

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Know before you go: 6 lessons for enterprise GenAI adoption

CIO

Lesson 1: Don’t start from scratch to train your LLM model Massive amounts of data and computational resources are needed to train an LLM. That makes it impractical to train an LLM from scratch. Training GPT-3 was heralded as an engineering marvel. One workaround is to build a system with multiple LLMs.