AI augmentation of human intelligence has already started – AI is already around us in the form of computer control systems of many kinds, is now rapidly escalating with AI Large Language Models like ChatGPT, and will accelerate very quickly from here – if we let it.
Writing with a Nemesis: Using ChatGPT to Strengthen Your Arguments
Reading Time: 4 minutes Are you getting tired of ChatGPT’s endless regurgitation of SEO-optimized articles and social media posts? Even ChatGPT is getting tired of that. Too many people use the trendy AI as a text generator. Too few use it as a highly capable writing partner that never sleeps. When I first ran into ChatGPT, I swore I’d never … Continue reading Writing with a Nemesis: Using ChatGPT to Strengthen Your Arguments
Sundar Pichai on A.I. being ‘more profound’ than fire | Fortune
In 2018, the Alphabet CEO pointed out how humans found a way to harness fire despite its perils. He sees the same happening with artificial intelligence.
Watch "A ChatGPT Alternative That's Free & Open Source!" on YouTube
In this video, I'm exploring the free and opensource alternative to ChatGPT called Open Assistant. It's designed to eventually be a true AI assistant. As users, we can help develop it out and improve it right now.
Open Assistant: https://open-assistant.io/
GitHub: https://github.com/LAION-AI/Open-Assistant
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#OpenAssistant #ChatGPT #GPT4
Just made ChatGPT available on our API! Our incredible team of builders has delivered 10x cheaper model than our existing GPT-3.5 models, through system-wide optimizations, making it easier to power as many applications as possible.https://t.co/dUSp7rLs1I— Mira Murati (@miramurati) March 1, 2023
Meet Paella, a Novel AI Text-to-Image Model That Uses a Speed-Optimized Architecture Allowing to Sample a Single Image in Less Than 500 ms While Having 573M Parameters - MarkTechPost
Recent advances in the diversity, quality, and variety of created pictures result from research on text-to-image generation. However, these models' remarkable output quality has come at the expense of poor inference speeds that are unsuitable for end-user applications due to their numerous sampling stages. Most recent state-of-the-art works are either transformer-based or rely on diffusion models. Transformers often compress their spatial representation before learning because the self-attention process scales quadratically with latent space dimensions. Additionally, a transformer flattens the encoded picture tokens to regard images as one-dimensional sequences, which is an unnatural projection of images and necessitates a substantially more
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Microsoft AI Research Introduces DeepSpeed-MII, A New Open-Source Python Library From DeepSpeed That Speeds Up 20,000+ Widely Used Deep Learning Models - MarkTechPost
While open-source software has made AI accessible to more people, there are still two significant barriers to its widespread use: inference delay and cost. System optimizations have come a long way and can substantially reduce latency and cost for DL model inference, but they are not immediately accessible. Many data scientists lack the expertise to correctly identify and implement the set of system optimizations relevant to a specific model, making low latency and low-cost inference primarily out of reach. The complex nature of the DL model inference landscape, including wide variations in model size, architecture, system performance characteristics, hardware requirements,
New model acts as search engine for large databases of pathology images, helping to identify rare diseases and which patients likely to respond to similar therapies
Check Out How These Illinois Tech AI Researchers Extracted Personal Information From Anonymous Cell Phone Data Using Machine Learning - MarkTechPost
Many people who regularly use social media, cell phones, home security cameras, and location trackers don't realize the full extent of their data. They have no idea that the information they have gathered can be replicated by others using machine learning (ML) techniques. The consequence is that users are always at risk of having their anonymized information de-anonymized by ML algorithms, although most people cherish their online privacy, albeit to varying degrees. Data security concerns have been raised after a team of researchers from the Illinois Institute of Technology used machine learning and artificial intelligence algorithms to extract personally identifiable