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

TechCrunch

8 questions to answer before your startup faces technical due diligence. After technical due diligence begins, no amount of storytelling can cover the secrets buried in GitHub and Jira. After technical due diligence begins, no amount of storytelling can cover the secrets buried in GitHub and Jira.

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Four investors explain why AI ethics can’t be an afterthought

TechCrunch

A founder recently told TechCrunch+ that it’s hard to think about ethics when innovation is so rapid: People build systems, then break them, and then edit. We’re widening our lens, looking for more investors to participate in TechCrunch surveys , where we poll top professionals about challenges in their industry.

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This week in AI: Amazon ‘enhances’ reviews with AI while Snap’s goes rogue

TechCrunch

Keeping up with an industry as fast-moving as AI is a tall order. This week in AI, Amazon announced that it’ll begin tapping generative AI to “enhance” product reviews. This week in AI, Amazon announced that it’ll begin tapping generative AI to “enhance” product reviews.

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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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Ethics of generative AI: To be innovative, you must first be trustworthy

CIO

Over the past year, generative AI – artificial intelligence that creates text, audio, and images – has moved from the “interesting concept” stage to the deployment stage for retail, healthcare, finance, and other industries. Before training GenAI models, personal identifiers should be removed or masked.

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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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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.