ML Engineer and tech writer Donato Riccio wrote an article entitled "The End of RAG?" discussing what might replace Retrieval Augmented Generation in the near future. The article was received as highly controversial within the AI echo chamber, so I brought Donato on the podcast to discuss RAG, why people are so obsessed with vector databases, and the upcoming research in AI that might replace it.

Takeaways:

• RAG is necessary due to LLMs' limited context window and scalability issues, and the need to avoid hallucinations and outdated information.
• Larger/infinite context window models and linear-scaling models (e.g. RWKV, Eagle) may allow for learning through forward propagation, allowing for more efficient and effective knowledge acquisition
• Agentic flows are likely far more powerful than RAG - and when they actually start working consistently, we may see the need for vector databases dramatically reduced.
• RAG libraries and abstracts can be helpful for getting off the ground but don't solve the hard problems in specific vertical LLM use cases.
• RAG vs Agents, and the complex ways that vertical AI approach RAG in practice

Share your thoughts with us at [email protected] or tweet us @slingshot_ai.

What’s going on with GPUs? We talk through the GPU bottleneck/supply gut, Meta’s apparent 600,000 H100-equivalents and the future of the GPU cloud.

Neel Master is the CEO and founder of Cedana, enabling pause/migrate/resume for compute jobs. Neel is a serial entrepreneur, former founder of Engooden and angel investor. He started his career in ML research at MIT's CSAIL.

Topics from this podcast include:

• Cedana's real-time save, migrate and resume for compute technology, enabling the migration of compute jobs across instances without interruption
• When will there be enough GPUs?
• What does it mean, that the cloud can become a robot?
• How might compute change, as per-capita GPU supply grows massively?
• How much does it actually cost to run GPUs?
• How can startups compete with the Big Tech’s giant compute moats?

Share your thoughts with us at [email protected] or tweet us @slingshot_ai.

Founders of Lingopal, Deven Orie and Casey Schneider, join to talk about their startup story, developing real-time translation software for enterprises.

Topics include:

• Why is translation so hard?
• How are enterprise and consumer AI products different (e.g. Google Translate vs Lingopal)?
• Should AI product companies be doing AI research?
• Is it safe to rely on open source?

Share your thoughts with us at [email protected] or tweet us @slingshot_ai.

Founder of the SafeLlama community, Enoch Kan joins us today, to talk about safety in open source and medical AI. Enoch previously worked in AI for radiology, focused on mammography at Kheiron Medical. Enoch is an open source contributor, and his substack is called Cross Validated.

Key topics they discuss include:

• New jailbreaks for LLMs appear every day. Does it matter?
• How do internet firewalls compare to AI “firewalls”?
• Why do human radiologists still exist? Would it be safe to replace them all today?
• Does safety matter more or less as models become more accurate?
• If regulation is too intense, could we end up with illegal consumer LLMs? For example, could we stop the masses from using an illegal AI doctor that you can access from your phone?

Share your thoughts with us at [email protected] or tweet us @slingshot_ai.

Join Daniel Cahn on another SlingTalk episode with Kristian Freed (ex-CTO at Pariti and Elder), discussing the past, present and future of AI-assisted or AI-driven software.

They talked about:

• The Evolution of Coding Tools: From basic text editors to advanced IDEs and the integration of AI tools like Co-Pilot.
• The Impact of AI on Software Development Practices: How AI is reshaping the way code is written and the process of software development.
• AI-Generated Code and Its Potential: Exploring the current capabilities of AI in generating code and its future implications.
• AI as a Mentor and Learning Aid: The role of AI in guiding developers through new languages and frameworks, acting like a digital coach.
• Challenges and Risks of AI in Software Development: Discussing the potential increase in mediocre code, security risks, and the future role of human oversight

Share your thoughts with us at [email protected] or tweet us @slingshot_ai.

In 1950, Alan Turing asked, “Can machines think?” He suggested the Imitation Game as a test to evaluate whether a machine can think, more commonly called the “Turing Test.” Today we ask, is the Turing Test outdated? Joining Slingtalks this week are Kristian Freed & Guilherme Freire, founding engineers at Slingshot. Guilherme argues against the Turing Test, Kristian argues in favor.

Key topics they discuss include:

• A recent paper claims that GPT-4 comes close to passing the Turing Test. Is the paper’s result valid? How close are we to passing the Turing Test?
• Defining the Turing Test and understanding the various iterations on its original framing since 1950. Are there levels in passing the Turing Test?
• Who is the Turing Test’s interrogator? And who is the human participant?
• If AI could pass the Turing Test, would that necessarily mean that most remote employees would be redundant?
• Is an AI’s ability to emulate human-like intelligence and deceive humans sufficient for intelligence? Is it necessary?
• What are the moral and philosophical implications of AI passing the Turing Test? Is intelligence morally significant? Is consciousness relevant?

Share your thoughts with us at [email protected] or tweet us @slingshot_ai.

Join Daniel Cahn on SlingTalks as he welcomes Jonathan Pedoeem (Founder of PromptLayer) to talk through Prompt Engineering. This episode offers an in-depth look into the past, present, and future of prompt engineering and the intricacies of crafting effective AI prompts.

Key topics they discuss include:

• Is prompt engineering more art or more science?
• The role of “prompt engineer” and whether prompt engineering is a highly specialized skill or a skill as common as Googling
• Approaches to evaluating prompts - in theory and in practice
• Techniques for AI-driven prompt engineering
• OpenAI’s new “GPTs” feature, and how it will change the landscape of prompt-engineered bots
• PromptLayer and dev tools for prompt engineering

Share your thoughts with us at [email protected] or tweet us @slingshot_ai.

Adam Kirsh (Head of Product & Engineering, Stealth Startup) joins Slingshot to talk about how AI is transforming investment due diligence.

Beyond AI in diligence, we discuss:

• “Horizontal” and “vertical” business models, that start from a point solution
• Building products vs. building relationships, and on being an AI partner for the enterprise
• AI-native startups and the reinvention of business models for the AI age
• Making incremental progress as a startup vs. visionary top-down redesigns of entire processes or even industries
• Consumer vs. enterprise applications of LLMs (analogy: iPhones vs Blackberrys)

We wrap up with some thought-provoking reflections and an open invitation for further discussion. We'd love to hear them! Drop an email at [email protected] or reach out on Twitter: @slingshot_ai.

Ex-Datadog Founding PM, Ayush Kapur, joins Daniel Cahn on SlingTalks to talk through the overloaded term, "Human in the Loop". They hone in on the impact of both, emotional and philosophical aspects of human interactions, for instance, your interaction with a doctor, and how those services can be considered irreplaceable by AI.

Key topics include:

• Human-in-the-loop as human review vs. partially automated processes
• Use cases where human-in-the-loop makes automation useless because humans have to repeat the exact same steps as the AI.
• Liability and “human-washing,” where a human-in-the-loop is used for masking decisions effectively made by AI.
• The psychological aspects of trusting a decision that's viewed as human vs. AI
• Future scenarios where decision-making is fully delegated to AI

Got something to say about AI and the human touch? Share your thoughts and reach out at [email protected] or tweet us @slingshot_ai. We want to hear from you!

AI is increasingly doing the heavy lifting in our communications and content generation. On this episode, Guilherme Freire, Founding ML Engineer at Slingshot, joins the podcast to discuss the impact of AI-generated content.

Some of the topics discussed:

• “Proof of Work” for humans, when AI makes personalization and connection too easy
• Potential for subpar AI-generated to put high-quality content creation out of business
• Hyper-personalized AI leading to greater divisiveness and bias; or on the flip side, for AI to serve as a "benevolent dictator" nudging us towards better habits and more diverse thinking
• The changing meaning of “free speech” in the age of AI
• The “Boring Utopia” eventuality, where AI processes scientific information at scale to generate new insights

Have thoughts? We'd love to hear them! Drop an email at [email protected] or reach out on Twitter: @slingshot_ai.