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WIRED on in tech
#EbolaPreventionMatters #CorporateAccountabilityMatters #PhilanthropyWithoutTransparencyIsNotPhilanthropy #CEOResponsibility #GlobalHealthMatters #Human #TechForGoodGoneWrong #InvestInPeopleNotProfit #WorldHealthExpertsSpeakOut #RegulateCEOPhilanthropyNow #MuskMustDoBetter #EbolaAIDSDeserveBetter #TransparencyIsKeyToSuccess #HumanRightsOverProfit

Discussion Points

  1. Accountability and Transparency: Is Elon Musk's admission of mistake sufficient to restore trust in his organization's humanitarian efforts, or does he need to take more concrete actions to rectify the situation?r
  2. Systemic Failures: How can organizations like SpaceX and Tesla prioritize profit over public health initiatives, and what systemic changes are needed to prevent similar mistakes in the future?r
  3. Global Health Priorities: Should corporations with significant influence and resources focus on supporting life-saving efforts, rather than prioritizing their own interests?r

Summary

Elon Musk's admission that he mistakenly fired Ebola prevention workers and quickly rectified the erroaises concerns about the state of humanitarian initiatives at SpaceX and Tesla. Despite this correction, many critical programs, including AIDS treatments for children, remain underfunded and inadequate.

The question remains whether Musk's organization can be trusted to prioritize public health over profit, and what steps should be taken to prevent similar failures in the future.

Elon Musk claims he mistakenly fired Ebola prevention workers, then quickly fixed the error. But Ebola programs are still in tatters, along with other livesaving efforts like AIDS treatments for child...

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darkreading on in hacking
#MachineUnlearningMatters #LLMForgottenImplications #AI #ResponsibleAIDevelopment #SelectivelyForgottenModels #LobbyizationOfLLMs #TheHumanTouchInAI #GovernanceForGoodInTech #TheFutureOfWorksWithValues #ForgetfulAIs #BigLanguageModelBlunders #Human #UnlearningEthics #LlamaConsequences

Discussion Points

  1. This content provides valuable insights about AI.
  2. The information provides valuable insights for those interested in AI.
  3. Understanding AI requires attention to the details presented in this content.

Summary

For you. Here it is:Discussion Points:r 1. The ethics of forgetting: How do we ensure that large language models don't forget important information, but rather learn to prioritize and discard irrelevant data?r 2.

Designing for forgetfulness: What technical approaches can be taken to implement "forgetting" mechanisms in large language models without compromising their performance?r 3. Human oversight and responsibility: Who is responsible when a large language model "forgets" something significant, and how can we ensure that humans are held accountable for such incidents?Summary:As we continue to develop large language models, it's essential to consider the implications of their ability to forget.

In the end, the question isn't whether large language models will ever forget — it's how we'll develop the tools and systems to do so effectively and ethically....

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