Recap: 2023 AI Highlights
This post revisits some of our most-liked articles this year. Read for a quick recap of the state of AI in 2023.
Dear readers,
As the year is approaching its end, we want to take a moment to reflect on the incredible journey we've embarked on together in the world of artificial intelligence. It's been a remarkable year filled with AI breakthroughs, challenges, and a growing sense of excitement for what the future holds. In this special end-of-the-year newsletter, we'll look back at some of the key highlights from this newsletter in 2023.
Wishing you a Happy New Year!
Ankur A. Patel
Here are our top 5 posts that you liked the best this year. Give them a read for a quick recap of the top AI developments of 2023.
1. GPT-4, GPT-3, and GPT-3.5 Turbo: A Review Of OpenAI's Large Language Models
OpenAI's GPT-4, released on March 13, 2023, outperforms its predecessors (GPT-3 Davinci and GPT-3.5 Turbo) in various aspects, including passing state bar exams in the 90th percentile, multimodality, and fewer errors. GPT-4 shows improvements in token span, reinforcement learning from human feedback (RLHF), and competitiveness against Google's Bard and Microsoft's Bing assistant.
2. PaLM 2 vs. GPT-4 vs. Claude 2 vs. Code LLaMA: Which Model Wins the LLM Race?
This comparison covers the latest LLMs: GPT-4, PaLM 2, Claude 2, and Code LLaMA. GPT-4 and PaLM 2 are state-of-the-art models with multimodal capabilities, while Claude 2 focuses on emotional intelligence, and Code LLaMA specializes in coding tasks. The article discusses the distinct advantages and use cases of each model, emphasizing their unique strengths and contributions to the LLM field.
3. LangChain: A Necessary Tool For Working With Large Language Models
LangChain is an open-source framework designed to build LLM-powered applications like ChatGPT. It introduces artificial reasoning capabilities, memory, and composability to LLMs, allowing for the development of more robust applications. LangChain's components include schema, models, prompts, indexes, memory, chains, and agents, each contributing to enhanced LLM functionality.
4. LLaMA 1 vs LLaMA 2: A Deep Dive into Meta’s LLMs
LLaMA 2, released by Meta in July 2023, is an evolution of LLaMA 1, focusing on efficiency and performance with fewer computing resources. Despite not outperforming GPT-4, LLaMA 2 shows significant improvements in safety and ethical guidelines adherence. It's an open-source model available for commercial and research use, trained using reinforcement learning from human feedback (RLHF) and a larger dataset.
5. The Impact of Wizard and Falcon on Open-Source LLM Development
WizardLM and Falcon models represent advancements in open-source LLM development. WizardLM, using the Evol-Instruct training method, is comparable to GPT-4 in various skills. Falcon, developed by TII, uses high-quality data from the RefinedWeb dataset, showcasing efficiency and performance on par with closed-source models. These developments indicate a significant potential for future open-source LLMs to rival or even outperform current models like GPT-4.
I also host an AI podcast and content series called “Pioneers.” This series takes you on an enthralling journey into the minds of AI visionaries, founders, and CEOs who are at the forefront of innovation through AI in their organizations.
To learn more, please visit Pioneers on Beehiiv.
These posts represent some of the key happenings in the artificial intelligence space. Large language models were the year’s highlight, with most companies pouring their resources into generative AI. Do check out our other posts for more AI insights.
Hope you enjoy reading these, and see you next year!