Monday, February 12, 2024

g-f(2)1959 Bridging the Credibility Canyon: Engineering Accountable Generative AI

 


genioux Fact post by Fernando Machuca and Claude


Introduction


Season 6, Episode 60 of Azeem Azhar's Exponential View titled "The Science of Making Truthful AI," examines approaches for constructing AI, especially large language models, that provide truthful and verifiable outputs - a pivotal challenge as adoption accelerates.



genioux GK Nugget


"The biggest problem of LLMs is that they will hallucinate...they cannot be trained every 5 minutes...and generative AI is only useful if the artifacts it produces are quick to verify." — Fernando Machuca and Claude



genioux Foundational Fact


Socher explores engineering solutions the company You.com implemented like leveraging web knowledge retrieval and citations to address key issues with generative models around imaginative confabulations, stale facts, and unverifiable sources.



Top 10 Relevant genioux Facts



  1. Future NLP progress depends on models reliably producing truthful outputs, not just stylistically convincing text.
  2. Lack of scientific rigor so far allows hallucinations that erode trust without accountability.
  3. Real-time updating requires architectures augmenting core LLMs with context like indexed web content.
  4. Citation functionality must discern the relevance and legitimacy of supporting sources.
  5. Regulating foundational research could hamper progress but applications warrant governance once real-world impacts grow.
  6. Despite the hype, transformational value requires extensive software engineering, not just captivating demos.
  7. Framing AI as an imminent existential threat distracts from addressing emerging real issues.
  8. Companies like You.com exemplify stacks blending open and proprietary technologies, indicating commoditization.
  9. Specialization and hybridization point to an ecosystem structure resembling traditional software.
  10. Attention should focus on the positive augmentation of human capabilities versus automation.




Conclusion


Constructing reliable generative models demands solutions tackling deep technical and ethical issues - progress depends on emphasizing scientific rigor alongside creativity.



REFERENCE

The GK Podcast


The Science of Making Truthful AIAzeem Azhar's Exponential View / Season 6, Episode 60, Harvard Business Review, February 7, 2024.



Azeem Azhar


Azeem Azhar is a renowned British entrepreneur, investor, and advisor with over 25 years of experience in the tech industry⁴. He is the creator of the highly-regarded newsletter, Exponential View³, which provides insights on the impact of technology on society and how it is changing the way we live¹².


Azhar's work has been profiled in prestigious publications such as The Economist, Financial Times, New York Times, WSJ, and MIT Technology Review³. He is also on the board of the Ada Lovelace Institute and several other firms³.


In his newsletter and podcasts, Azhar shares his analysis of tech and social trends that he believes will shape our future¹². His discussions range from AI adoption and the emergence of new business models around AI, to decentralization technologies and the energy transition¹.


Azhar is also known for his work on building truthful and verifiable AI systems². He has had conversations with leading figures in the field, shedding light on the critical breakthroughs in AI and the technical challenges of ensuring AI's reliability².


In summary, Azeem Azhar is a visionary who is deeply involved in understanding and shaping the future of technology and its impact on society. 🌐💡


Source: Conversation with Bing, 2/13/2024

(1) Azeem Azhar | Technology Speaker | Chartwell Speakers Bureau. https://www.chartwellspeakers.com/speaker/azeem-azhar/.

(2) Exponential View - Harvard Business Review. https://hbr.org/2019/04/podcast-exponential-view.

(3) Azeem’s 2024 Trends: AI, Energy, and Decentralization. https://hbr.org/podcast/2024/01/azeems-2024-trends-ai-energy-and-decentralization.

(4) The Science of Making Truthful AI - Harvard Business Review. https://hbr.org/podcast/2024/02/the-science-of-making-truthful-ai.

(5) Azeem Azhar - EverybodyWiki Bios & Wiki. https://en.everybodywiki.com/Azeem_Azhar.





Copilot's Summary


In Season 6, Episode 60 of Azeem Azhar's Exponential View titled "The Science of Making Truthful AI," Azhar engages in a conversation with Richard Socher, CEO and founder of You.com¹. The episode delves into the complexities of building AI systems that are both truthful and verifiable¹.


Key points discussed in the episode include:

  • The critical breakthroughs in AI and the technical challenges of ensuring AI’s reliability¹.
  • The future of search as envisioned by Socher¹.
  • The role of scientific rigor in the current and future developments of large language models¹.
  • The founding of You.com and its mission to revolutionize search¹.
  • Predictions for the next big breakthroughs in AI¹.


This episode provides valuable insights into the rapidly evolving field of AI and the importance of truthfulness and verifiability in AI systems¹. 🌐💡


Source: Conversation with Bing, 2/13/2024

(1) The Science of Making Truthful AI - Harvard Business Review. https://hbr.org/podcast/2024/02/the-science-of-making-truthful-ai.

(2) Learning from 2021: Azeem’s Takeaways - Harvard Business Review. https://hbr.org/podcast/2021/12/learning-from-2021-azeems-takeaways.

(3) All episodes of Azeem Azhar's Exponential View - Chartable. https://chartable.com/podcasts/exponential-view/episodes.

(4) AI Takes the Wheel: New Advances in Autonomous Driving. https://hbr.org/podcast/2023/12/ai-takes-the-wheel-new-advances-in-autonomous-driving.



The categorization and citation of the genioux Fact post


Categorization


This genioux Fact post is classified as Bombshell Knowledge which means: The game-changer that reshapes your perspective, leaving you exclaiming, "Wow, I had no idea!"



Type: Bombshell Knowledge, Free Speech


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References


genioux facts”: The online program on "MASTERING THE BIG PICTURE OF THE DIGITAL AGE”, g-f(2)1959, Fernando Machuca and ClaudeFebruary 12, 2024, Genioux.com Corporation.
 
The genioux facts program has established a robust foundation of over 1958 Big Picture of the Digital Age posts [g-f(2)1 - g-f(2)1958].



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