Daily Digest: What AI legends fear

PLUS: new coding champion is fast

November 01, 2023

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Daily Digest #275

Hello folks, here’s what we have today;

PICKS

  1. AI Halloween - Andrew Ng fears the sensationalist claims about human extinction are doing more harm than good. Andrew evaluates the legitimate risks while calling out fear-mongering and financial incentives behind it.🍿Our Summary (also below)

  2. Phind Model beats GPT-4 at coding - Phind's new code generation model beats GPT-4 at coding tasks while running 5x faster at 100 tokens/second. Beyond the benchmarks, Phind claims real users find the Phind Model as helpful as GPT-4 for answering technical coding questions.🍿Our Summary (also below)

  3. The executive order aftermath:

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  • LlamaIndex - Helping developers build applications using LLMs and their data.

NEWS
QUICK BITES

In the past few days, the heat between legends of the AI realm has been increasing. The battle is about the risks of AI. Andrew Ng, the co-founder of Google Brain and Coursera believes that big tech is pushing the human extinction by AI theme for their benefit and other researchers are adding fuel to the fire.

What is going on here?

Andrew believes while AI risks exist, fear-mongering causes overblown anxiety. Baseless warnings of AI-driven human extinction could impede AI progress that benefits humanity.

What does this mean?

Sincerity exists, but so do individuals/organizations who have strong financial incentives by overflowing the human extinction and superintelligent AI stories. Here’s a quick list of some legitimate fears and solutions in progress:

1) Hallucination that leads to misinformation, but developers are improving models and adding filters.

2) Easy access to tools for cybercrime: deepfakes, voice clones, malicious bots etc. Governments and companies are diverting resources to red teaming.

3) Copyright disputes for training data breach trust, but companies are finding legal ways to access data.

4) Fears that AI will eliminate human jobs are exaggerated since AI tends to transform jobs rather than replace them outright.

5) AI startup hype may lead to a correction, but the usefulness of generative AI means it's here to stay.

Why should I care?

While the researchers are debating pro and cons like they are their dorm room, take a step away. Think about who has what incentives. Dig deep to evaluate if the claims hold on basic interrogation.

If you’re a student, a builder, or a developer, focus on finding the legitimate fears and facing them head-on.

Scary Goofball AI - Fun little games for Halloween made by GPT-4, DallE-3 and Midjourney.

QUICK BITES

Phind has released a new model for code generation that matches or exceeds GPT-4 in quality while being much faster. Beyond the benchmarks, Phind claims real users find the Phind Model as helpful as GPT-4 for answering technical coding questions. Phind is a search engine + pair programmer using AI to help developers.

What is going on here?

Phind's new code generation model beats GPT-4 at coding tasks while running 5x faster at 100 tokens/second.

What does this mean?

The Phind Model V7 achieves a 74.7% accuracy on the HumanEval benchmark. The model is built on top of Phind’s earlier finetunes of CodeLlama-34B. After additional fine-tuning on 70B tokens of code, the Phind Model V7 now provides GPT-4 level responses in 10 seconds rather than 50. This speed boost comes from optimizing the model to run on NVIDIA H100s using the TensorRT-LLM library.

The Phind Model also supports up to 16k context, allowing for more detailed coding questions. Currently, 12k tokens are enabled for input on the website with 4k reserved for search results.

Why should I care?

Phind agrees there are still some rough edges, for example on certain challenging questions, the Phind Model might take more generations to get to the right answer than GPT-4.

Even with those limitations, getting GPT-4 level answers in 5x less time is impressive. Access to a larger context also allows including more code samples and details in your questions.

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