Starling-7B: UC Berkeley’s New Open-Source LLM

How do you copy GPT-4 without actually copying the model weights? In this article, you’ll learn how! πŸ’‘ Researchers from UC Berkeley have unveiled Starling-7B, an innovative large language model (LLM) trained using Reinforcement Learning from AI Feedback (RLAIF), as opposed to the Reinforcement Learning from Human Feedback (RLHF) approach used by many competitors. Starling-7B … Read more

Top 7 OpenAI Competitors That Pay Multiple Six Figures

The landscape of AI technology is rapidly evolving, with several companies emerging as key competitors to OpenAI. Each of these competitors brings unique strengths and approaches to the field, challenging OpenAI’s dominance in various ways. What are some good companies, apart from OpenAI, to work for and participate in the growth of the AI industry? … Read more

Code Llama 2: Examples and Playground (Try It Yourself)

Try It Yourself You can run the code llama 2 code completion model right here on the Finxter blog: If the embedding doesn’t work for some reason, check out this URL of the Huggingface space. Example Fibonacci I have asked Code Llama 2 to complete my code “def fibonacci(n)” and it did it flawlessly! See … Read more

State of AI Report 2023: 163 Pages Reduced to 17 Visuals (Executive Summary)

The State of AI Report 2023, encapsulates vital AI advancements in research, industry, and politics. It underscores GPT-4’s triumph, NVIDIA’s ascension to a $1T market cap due to GPU demand, and the proliferating open-source AI community with 32M LLaMa model downloads on Hugging Face in a month. While Chat-GPT emerges as a developer favorite, GenAI’s … Read more

Human Software Developers vs ChatGPT – Who’s Better in Fixing GitHub Pull Requests?

In the age of alien technology — large language models (LLMs), advanced AI and machine learning — it’s easy to fall into the belief that human roles, especially in tasks like software engineering, are on the verge of being replaced. I’m definitely guilty of prematurely announcing various job roles dead, even though they are not … Read more

The War between Tech Deflation & Monetary Inflation βš”οΈ Puts This Guardian on the Map πŸ›‘οΈ

We live in fascinating times. Turn on the news, and it often feels like the world is on a downward spiral. Stock markets wavering, geo-political tensions, and the looming specter of inflation. But let me let you in on a secret: there’s a significant mismatch between perception and reality. The Rise and Rise of Tech … Read more

Chain-of-Verification: This Novel Prompting Technique Fights Hallucinations in LLMs

Large language models (LLMs) often hallucinateβ€”generating plausible yet incorrect information. Recent research by Meta AI researchers explores a promising technique to address this issue, termed Chain-of-Verification (CoVe). Quick Overview of Chain-of-Verification (CoVe) CoVe takes a systematic approach to enhance the veracity of the responses generated by large language models. It’s a four-step dance: This technique … Read more

BitVM – Smart Contracts on Bitcoin Without Hard Fork

πŸ§‘β€πŸ’» TLDR: The BitVM whitepaper by Bitcoin developer Robin Linus introduces a method to implement Ethereum-like smart contracts on Bitcoin without a hard fork. BitVM proposes a system where contract logic is executed off-chain but verified on Bitcoin, similar to Ethereum’s optimistic rollups, BitVM enables Turing-complete Bitcoin contracts. The architecture employs fraud proofs and a … Read more

How Many Publications Does One Need to Get a Ph.D. in Computer Science?

The following answer is based on my experience as a doctoral researcher in distributed systems. Computer science is a big field with vast differences in the quality and quantity requirements of your Ph.D. supervisor. Having said this, you’ll probably need somewhere between two to five publications to get a Ph.D. in computer science. I have … Read more

Transformer vs Autoencoder: Decoding Machine Learning Techniques

An autoencoder is a neural network that learns to compress and reconstruct unlabeled data. It has two parts: an encoder that processes the input, and a decoder that reproduces it. While the original transformer model was an autoencoder with both encoder and decoder, OpenAI’s GPT series uses only a decoder. In a way, transformers are … Read more