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
💡 Prompt engineering is an emerging field in artificial intelligence (AI), focused on the art of crafting effective prompts to optimize the performance of large language models (LLMs). These AI models rely on inputs called prompts to generate accurate outputs. A skilled prompt engineer would possess the ability to iterate and refine prompts to ensure … Read more
Large language models (LLMs) often hallucinate—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
Welcome to the ultimate video guide on the groundbreaking book “Deep Learning” by Ian Goodfellow, Yoshua Bengio, and Aaron Courville! Why “Deep Learning” the book? It’s the definitive textbook in the field, “Deep Learning” covers a comprehensive range of topics, from the foundational concepts to the advanced techniques driving the latest innovations in artificial intelligence. … Read more
🧑💻 10 Steps Learning Path: Do you want to learn Python but are unsure where to start? I’ve curated an optimal learning path, taking you from a complete beginner to an advanced Python programmer using Finxter Academy courses with downloadable PDF certificates. All courses can be freely accessed by Finxter Premium Members (no restrictions). Level … Read more
Example 1 – “Find Bug in Code Screenshot” In the following ChatGPT interaction, I tried pasting an image of a code snippet with a bug. Note that I didn’t paste the code, only the screenshot of the code as an image! I also gave it the prompt “Find the bug!“. First, it does fix the … Read more
🧑💻 A Note on the Tech Stack: This is my recent project where I used OpenAI API to create two personas playing the role of AI professors, Alice and Bob, that are experts in philosophy and ethics. Then I let the two large language models (LLMs) debate against each other and recorded the debate. I … Read more
Llama 2 is the next generation of our open-source large language model. It is available for free for research and commercial use. Inside the Llama 2 model, you’ll find pretrained and fine-tuned language models like Llama Chat and Code Llama. These models range from 7B to 70B parameters and have been trained on 2 trillion … Read more
In the US, 59.8 percent of the workforce are white collar workers. Most of them will eventually be disrupted by AI tools. Many of them can already be replaced by large language models as shown in recent research: This will release much of the work in our society and causes significant prosperity for society overall. … Read more
The integration of Large Language Models (LLMs) into software systems introduces a paradigm where stochastic programming becomes a focal point, challenging the deterministic norms that have long been foundational in software engineering. Traditional software engineering approaches, such as unit testing, are predicated on the ability to predict outputs given certain inputs, ensuring that the software … Read more
This learning path will teach you the skills to be the core foundation of a profitable new career in the upcoming decade of rapid change. Our proposed learning path focuses on developing skills in Python, OpenAI, and related technologies to master prompt engineering. Let’s be on the right side of change! 🚀 All courses can … Read more
Open-source research on large language models (LLMs) is crucial for democratizing this powerful technology. Although open-source LLMs are now widely used and studied, they faced initial challenges and criticism. Early attempts at creating open-source LLMs like OPT and BLOOM had poor performance compared to closed-source models. This led researchers to realize the need for higher-quality … Read more