Chadwick Vorman

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I. Almeida
“The lack of transparency regarding training data sources and the methods used can be problematic. For example, algorithmic filtering of training data can skew representations in subtle ways. Attempts to remove overt toxicity by keyword filtering can disproportionately exclude positive portrayals of marginalized groups. Responsible data curation requires first acknowledging and then addressing these complex tradeoffs through input from impacted communities.”
I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

I. Almeida
“It is critical to recognize the limitations of LLMs from a consumer perspective. LLMs only possess statistical knowledge about word patterns, not true comprehension of ideas, facts, or emotions. Their fluency can create an illusion of human-like understanding, but rigorous testing reveals brittleness. Just because a LLM can generate coherent text about medicine or law doesn’t mean it grasps those professional domains. It does not. Responsible evaluation is essential to avoid overestimating capabilities.”
I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

I. Almeida
“Every piece of data ingested by a model plays a role in determining its behavior. The fairness, transparency, and representativeness of the data reflect directly in the LLMs' outputs. Ignoring ethical considerations in data sourcing can inadvertently perpetuate harmful stereotypes, misinformation, or gaps in knowledge. It can also infringe on the rights of data creators.”
I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

I. Almeida
“LLMs represent some of the most promising yet ethically fraught technologies ever conceived. Their development plots a razor’s edge between utopian and dystopian potentials depending on our choices moving forward.”
I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

I. Almeida
“For businesses, it is vital to embed ethical checkpoints in workflows, allowing models to be stopped if unacceptable risks emerge. The apparent ease of building capable LLMs with existing foundations can mask serious robustness gaps. However unrealistic the scenario may seem under pressure, responsible LLM work requires pragmatic commitments to stop if red lines are crossed during risk assessment.”
I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

1865 SciFi and Fantasy Book Club — 42725 members — last activity 29 minutes ago
Hi there! SFFBC is a welcoming place for readers to share their love of speculative fiction through group reads, buddy reads, challenges, ...more
4170 The Sword and Laser — 21665 members — last activity 2 hours, 23 min ago
Online discussion forum for the Sword and Laser podcast and monthly book club pick. Subscribe to the audio podcast: http://itunes.apple.com/us/podca ...more
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This group is dedicated to connecting readers with Goodreads authors. It is divided by genres, and includes folders for writing resources, book websit ...more
45059 Sci-fi and Heroic Fantasy — 8853 members — last activity 1 hour, 21 min ago
A place for those who walk the green forests of Middle Earth, cross the pale sands of Arrakis, sail the blue waters of Earthsea, slip among the shadow ...more
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This group is for like-minded people who want to read all of the Hugo and Nebula winners and runners-up. The Hugo Awards are chosen by the fans. The ...more
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Introduction to Large Language Models for Business Leaders by I. Almeida
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