The Harsh Reality of Being an ML Researcher
Author(s): Boris Meinardus Originally published on Towards AI. What you need to expect when entering the field of ML research. We all know that Machine Learning is the hottest thing to work on right now. And if you are a researcher, especially …
This AI newsletter is all you need #85
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, attention was on the emerging competition for OpenAI’s GPT-4 and GPTStore in the form of Google’s Gemini Ultra and Hugging Face’s Hugging …
Google Finally Challenges ChatGPT
Author(s): Ignacio de Gregorio Originally published on Towards AI. A turning point for AI? It finally happened. A few months after Google announced Gemini, its Gemini Pro online version has reached the podium of best models, surpassing some GPT-4 versions and coming …
My Experience with the Apple Vision Pro and Future Perspectives in Computer Vision and Healthcare
Author(s): Alberto Paderno Originally published on Towards AI. Just me and the Apple Vision Pro “It was a rainy day in Palo Alto. The line in front of the Apple Store was interminable, and only a few strong-willed people could be persistent …
Decoding AI Beyond Buzzwords for Absolute Beginners 2024
Author(s): Mélony Qin (aka cloudmelon) Originally published on Towards AI. Artificial intelligence (AI) has become one of the most fascinating areas in today’s fast-paced world. We know that artificial intelligence can seem overwhelming in many ways, especially with so many buzzwords. In …
Attention Mechanism
Author(s): Dr Barak Or Originally published on Towards AI. Attention Mechanism Self Attention -concept At the heart of the Transformer model lies the attention mechanism, a pivotal innovation designed to address the fundamental challenge of learning long-range dependencies within sequence transduction tasks. …
H2O.ai’s Danube and The Case for Smaller, More Accessible AI Models
Author(s): Frederik Bussler Originally published on Towards AI. Photo by Agence Olloweb on Unsplash AI models have grown massively in size in recent years, with models like GPT-3 containing over 175 billion parameters (and an estimated 1 trillion in GPT-4). However, these …
![[Code Llama 70B🦙] It is One Step Away From Surpassing GPT-4](https://miro.medium.com/v2/resize:fit:700/1*VbCCJPI8eYdUVUmq24b8MQ.png "[Code Llama 70B🦙] It is One Step Away From Surpassing GPT-4")
[Code Llama 70B🦙] It is One Step Away From Surpassing GPT-4
Author(s): Gao Dalie (高達烈) Originally published on Towards AI. When one thinks about the development of artificial intelligence models, the two names that initially come to mind are OpenAI and, perhaps, Google. However, they are not the only ones. In this Post, …
How to Detect the Trend in the Time Series Data and Detrend in Python
Author(s): Rashida Nasrin Sucky Originally published on Towards AI. Photo by Polly Alexandra on Unsplash Before choosing any time series forecasting model, it is very important to detect the trend, seasonality, or cycle in the data. Half the job is to understand …
Learn AI Together — Towards AI Community Newsletter #10
Author(s): Towards AI Editorial Team Originally published on Towards AI. This week, I had a fantastic discussion with Mariam Brian, an amazing artist and CEO of Holo Art. This episode is perfect for those curious about how AI is not just a …
Productionizing Generative AI Applications
Author(s): Marie Stephen Leo Originally published on Towards AI. 5 Practical, Beginner-Friendly Tips to Transform Your Generative AI Projects!Image generated by Author using Dall E 3 with manual edits for text Over the past year, I’ve been building and scaling customer-facing GenAI …
What Are Dimensions in Machine Learning?
Author(s): Max Charney Originally published on Towards AI. Source: https://www.reddit.com/r/machinelearningmemes/comments/taelzq/ml_scientists_when_their_excel_spreadsheet_has_4/ Introduction When I first started reading papers involving deep learning, I often encountered discussions about high-dimensions (feature spaces) and models such as SqueezeNet. I’m pretty sure data can’t be captured in the …
Meta’s Self-Rewarding Models, the Key to SuperHuman LLMs?
Author(s): Ignacio de Gregorio Originally published on Towards AI. Meta, the company behind Facebook, Whatsapp, and Rayban’s Meta glasses, has announced a recent, highly promising AI breakthrough, Self-Rewarding Language Models. Their results have allowed their LLaMa-2 70B fine-tuned model to surpass models …
Generative AI Terminology — An Evolving Taxonomy To Get You Started
Author(s): Abhinav Kimothi Originally published on Towards AI. Being new to the world of Generative AI, one can feel a little overwhelmed by the jargon. I’ve been asked many times about common terms used in this field. To help ease the psychological …
Can ChatGPT Solve Mensa Puzzles?
Author(s): Jim the AI Whisperer Originally published on Towards AI. Daily Challenges: AI vs. Mensa Calendar Puzzles The elephant in the room with AI is: what even is “intelligence”? I’m sure everyone is familiar with the Turing Test, which LLMs have pretty …
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