Tag: GPT-3
Cerebras Hits the Accelerator for Deep Learning Workloads
When it comes to large neural networks like BERT or GPT-3, organizations often must wait weeks or even months for a training task to complete if they’re using traditional CPU and GPU clusters. But with its massive Wafe Read more…
An All-Volunteer Deep Learning Army
A team of researchers says their novel framework, called Distributed Deep Learning in Open Collaborations, or DeDLOC, brings the potential to train large deep learning models from scratch in a distributed, grid-like mann Read more…
Inside eBay’s Optimization Techniques for Scaling AI
Getting the software right is important when developing machine learning models, such as recommendation or classification systems. But at eBay, optimizing the software to run on a particular piece of hardware using disti Read more…
Unlocking the True Potential of ML: How Self-Supervised Learning in Language Can Beat Human Performance
A core goal for many organizations using artificial intelligence (AI) systems is to have them mirror human language and intelligence. However, mimicking human language and mastering its unique complexities continues to b Read more…
Deci Shows a NAC for Automated Neural Net Construction
Deep learning researchers have been dancing around a looming performance wall in recent months, as huge neural networks push the limits in terms of computation and power consumption. But now a company called Deci says it Read more…
The Perfect Storm: How the Chip Shortage Will Impact AI Development
This chip shortage has brought to light our dependency on hardware to run high-tech economies and the everyday lives of consumers. Today, chips can be found in everything from gaming consoles like Xbox Series, PlayStatio Read more…
Google’s ‘Breakthrough’ LaMDA Promises to Elevate the Common Chatbot
Many of Google’s language processing efforts – like BERT and, more recently, MUM – are focused on returning search queries. But as Google moves more toward Assistant – and search queries in general become more de Read more…
Experts Disagree on the Utility of Large Language Models
Large language models like OpenAI’s GPT-3 and Google Brain’s Switch Transformer have caught the eye of AI experts, who have expressed surprise at the rapid pace of improvement. However, not everybody is jumping onto the bandwagon, and others see significant limitations in the new technology, as well as ethical implications. Read more…
AI Experts Discuss Implications of GPT-3
Last July, GPT-3 took the internet by storm. The massive 175 billion-parameter autoregressive language model, developed by OpenAI, showed a startling ability to translate languages, answer questions, and – perhaps most Read more…
One Model to Rule Them All: Transformer Networks Usher in AI 2.0, Forrester Says
The recent advent of massive transformer networks is ushering in a new age of AI that will give customers advanced natural language capabilities with just a fraction of the skills and data previously required, according Read more…
Google’s New Switch Transformer Model Achieves 1.6 Trillion Parameters, Efficiency Gains
Last year, OpenAI wowed the world with its eerily human language generator, GPT-3. The autoregressive model stood at a then-staggering 175 billion parameters, ten times higher than its predecessors. Now, Google is upping Read more…
Low-Code Can Lower the Barrier to Entry for AI
Organizations that want to get started quickly with machine learning may be interested in investigating emerging low-code options for AI. While low-code techniques will never completely replace hand-coded systems, they c Read more…
OpenAI’s GPT-3 Language Generator Is Impressive, but Don’t Hold Your Breath for Skynet
Just a couple of months after releasing a paper describing GPT-3, AI development and deployment company OpenAI has begun testing its novel, AI-powered language generator with a select group of users through a private bet Read more…
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