Artificial intelligence is helping American cops look for “suspicious” patterns of movement, digging through license plate databases with billions of records. A drug trafficking case in New York has uncloaked — and challenged — one of the biggest rollouts of the controversial technology to date.
InMarch of 2022, David Zayas was driving down the Hutchinson River Parkway in Scarsdale. His car, a gray Chevrolet, was entirely unremarkable, as was its speed. But to the Westchester County Police Department, the car was cause for concern and Zayas a possible criminal; its powerful new AI tool had identified the vehicle’s behavior as suspicious.
Searching through a database of 1.6 billion license plate records collected over the last two years from locations across New York State, the AI determined that Zayas’ car was on a journey typical of a drug trafficker. — Read More
Monthly Archives: August 2023
Introducing SeamlessM4T, a Multimodal AI Model for Speech and Text Translations
The world we live in has never been more interconnected, giving people access to more multilingual content than ever before. This also makes the ability to communicate and understand information in any language increasingly important.
Today, we’re introducing SeamlessM4T, the first all-in-one multimodal and multilingual AI translation model that allows people to communicate effortlessly through speech and text across different languages. — Read More
Stable Diffusion -XL 1.0-base
SDXL consists of an ensemble of experts pipeline for latent diffusion: In a first step, the base model is used to generate (noisy) latents, which are then further processed with a refinement model (available here: https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0/) specialized for the final denoising steps. Note that the base model can be used as a standalone module.
Alternatively, we can use a two-stage pipeline as follows: First, the base model is used to generate latents of the desired output size. In the second step, we use a specialized high-resolution model and apply a technique called SDEdit (https://arxiv.org/abs/2108.01073, also known as “img2img”) to the latents generated in the first step, using the same prompt. This technique is slightly slower than the first one, as it requires more function evaluations. — Read More
Source code is available at https://github.com/Stability-AI/generative-models .
Reinforced Self-Training (ReST) for Language Modeling
Reinforcement learning from human feedback (RLHF) can improve the quality of large language model’s (LLM) outputs by aligning them with human preferences. We propose a simple algorithm for aligning LLMs with human preferences inspired by growing batch reinforcement learning (RL), which we call Reinforced Self-Training (ReST). Given an initial LLM policy, ReST produces a dataset by generating samples from the policy, which are then used to improve the LLM policy using offline RL algorithms. ReST is more efficient than typical online RLHF methods because the training dataset is produced offline, which allows data reuse. While ReST is a general approach applicable to all generative learning settings, we focus on its application to machine translation. Our results show that ReST can substantially improve translation quality, as measured by automated metrics and human evaluation on machine translation benchmarks in a compute and sample-efficient manner. — Read More
Is the AI boom already over?
Generative AI tools are generating less interest than just a few months ago.
When generative AI products started rolling out to the general public last year, it kicked off a frenzy of excitement and fear.
People were amazed at the images and words these tools could create from just a single text prompt. Silicon Valley salivated over the prospect of a transformative new technology, one that it could make a lot of money off of after years of stagnation and the flops of crypto and the metaverse. And then there were the concerns about what the world would be after generative AI transformed it. Millions of jobs could be lost. It might become impossible to tell what was real or what was made by a computer. And if you want to get really dramatic about it, the end of humanity may be near. We glorified and dreaded the incredible potential this technology had. — Read More
Developers are now using AI for text-to-music apps
With the rise in popularity of Large Language Models (LLMs) and generative AI tools like ChatGPT, developers have found use cases to mold text in different ways for use cases ranging from writing emails to summarizing articles. Now, they are looking to help you generate bits of music by just typing some words.
Brett Bauman, the developer of PlayListAI (previously LinupSupply), launched a new app called Songburst on the App Store this week. The app doesn’t have a steep learning curve. You just have to type in a prompt like “Calming piano music to listen to while studying” or “Funky beats for a podcast intro” to let the app generate a music clip. — Read More
AI2 drops biggest open dataset yet for training language models
Language models like GPT-4 and Claude are powerful and useful, but the data on which they are trained is a closely guarded secret. The Allen Institute for AI (AI2) aims to reverse this trend with a new, huge text dataset that’s free to use and open to inspection.
Dolma, as the dataset is called, is intended to be the basis for the research group’s planned open language model, or OLMo (Dolma is short for “Data to feed OLMo’s Appetite). As the model is intended to be free to use and modify by the AI research community, so too (argue AI2 researchers) should be the dataset they use to create it. — Read More
Exactly the Wrong AI Copyrightability Case
Creativity Machine guy assumed away the debate and lost
Friday’s trial-court decision in Thaler v. Perlmutter, case 22-1564 in the DC district court, epitomizes the sad fact that just the wrong situation can make bad headlines easy, well before the real work in a legal debate.
I’m sure there will be links like “Court Rules AI Art Can’t Be Copyrighted” aplenty. They will be wrong. The court didn’t rule that AI art can’t be copyrighted. It ruled that copyright requires human authorship, surprising approximately zero copyright lawyers…or people who have read the Wikipedia page. — Read More
Shah Rukh Khan endorsing local businesses – with AI advertising
Does ChatGPT have a liberal bias?
A new paper making this claim has many flaws. But the question merits research.
Previous research has shown that many pre-ChatGPT language models express left-leaning opinions when asked about partisan topics. But OpenAI said in February that the workers who fine-tune ChatGPT train it to refuse to express opinions when asked controversial political questions. So it was interesting to see a new paper claim that ChatGPT expresses liberal opinions, agreeing with Democrats the vast majority of the time. — Read More
Rick's Cafe AI 