Amjad Masad & Adam D’Angelo: How Far Are We From AGI?
Adam D’Angelo (Quora/Poe) thinks we're 5 years from automating remote work. Amjad Masad (Replit) thinks we're brute-forcing intelligence without understanding it.
In this conversation, two technical founders who are building the AI future disagree on almost everything: whether LLMs are hitting limits, if we're anywhere close to AGI, and what happens when entry-level jobs disappear but experts remain irreplaceable. They dig into the uncomfortable reality that AI might create a "missing middle" in the job market, why everyone in SF is suddenly too focused on getting rich to do weird experiments, and whether consciousness research has been abandoned for prompt engineering.
Plus: Why coding agents can now run for 20+ hours straight, the return of the "sovereign individual" thesis, and the surprising sophistication of everyday users juggling multiple AIs.
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Bringing AI to the Masses with Adam D’Angelo
Generative AI has initiated a transformative shift, reshaping our world in unprecedented ways. In a16z's AI Revolution series, we engage some of the most impactful builders in the field of AI discussing and debating where we are, where we’re going, and the big open questions in AI.
In this episode, General Partner David George chats with Adam D'Angelo, the CEO and founder of Quora, wade into this fast-moving AI landscape, and specifically touch on how building infrastructure for creators can democratize AI.
Adam, who is now building AI aggregator Poe and is on the board of OpenAI, has long been paying attention to this AI wave. He recounts this evolving fascination, and together Adam and David explore the dynamic synergy between humans and AI, highlighting the critical role of experimentation for founders in the AI realm.
As a reminder, this conversation comes from our AI Revolution series, which you can dive into more deeply at a16z.com/ai.
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Xavier Amatriain — Building AI-powered Primary Care
Xavier shares his experience deploying healthcare models, augmenting primary care with AI, the challenges of "ground truth" in medicine, and robustness in ML.
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Xavier Amatriain is co-founder and CTO of Curai, an ML-based primary care chat system. Previously, he was VP of Engineering at Quora, and Research/Engineering Director at Neflix, where he started and led the Algorithms team responsible for Netflix's recommendation systems.
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⏳ Timestamps:
0:00 Sneak peak, intro
0:49 What is Curai?
5:48 The role of AI within Curai
8:44 Why Curai keeps humans in the loop
15:00 Measuring diagnostic accuracy
18:53 Patient safety
22:39 Different types of models at Curai
25:42 Using GPT-3 to generate training data
32:13 How Curai monitors and debugs models
35:19 Model explainability
39:27 Robustness in ML
45:52 Connecting metrics to impact
49:32 Outro
🌟 Show notes:
- http://wandb.me/gd-xavier-amatriain
- Transcription of the episode
- Links to papers, projects, and people
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Bridging the Patient-Physician Gap with ML and Expert Systems w/ Xavier Amatriain - #316
Today we’re joined by return guest Xavier Amatriain, Co-founder and CTO of Curai, whose goal is to make healthcare accessible and scaleable while bringing down costs. In our conversation, we touch on the shortcomings of traditional primary care, and how Curai fills that role, and some of the unique challenges his team faces in applying ML in the healthcare space. We also discuss the use of expert systems, how they train them, and how NLP projects like BERT and GPT-2 fit into what they’re building.
Xavier Amatriain - Engineering Practical Machine Learning Systems - TWiML Talk #3
My guest this time is Xavier Amatriain. Xavier is a former researcher who went on to lead the machine learning recommendations team at Netflix, and is now the vice president of engineering at Quora, the Q&A site. We spend quite a bit of time digging into each of these experiences in the interview. Here are just a few of the things we cover in our discussion: Why Netflix invested $1 million in the Netflix Prize, but didn’t use the winning solution; What goes into engineering practical machine learning systems; The problem Xavier has with the deep learning hype; And, what the heck is a multi-arm bandit and how can it help us. The notes for this show can be found at https://twimlai.com/talk/3.