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Jurassic: A Guide to AI21's large language models
New technologies and models are emerging that push the boundaries of what is possible. One such model is Jurassic-2, developed by AI21 Studios
Jurassic-2 (J2) is one of many new AI programs based on large language models (LLMs), like ChatGPT and Gemini. J2 is the brainchild of AI21 Studios and is a jack-of-all-trades large language model that provides realistic, human-like interactions. It's used to build frameworks for advanced LLM-powered AI agents with natural language processing capabilities. Jurassic-2 models are classified as general-purpose, meaning they can be trained and tuned to meet any need.
How does semi-supervised-learning work in Machine Learning?
Data is everywhere, and there is not a drop to drink; thankfully, semi-supervised learning can save the day
Machine learning has become integral to our daily lives, quietly shaping experiences from Netflix's personalized movie recommendations to the facial recognition technology on flagship Android phones. However, behind the scenes, these advanced systems require tons of data and hours of work to label and format this data for practical training.
Machine learning is revolutionizing how computers perform tasks traditionally considered exclusive to human intelligence. Our everyday lives are deeply embedded with machine learning, from AI chatbot apps that assist to spam filters for our emails and phones with AI features. But what exactly is machine learning? This article explains what machine learning is and how it works.
Google Gemini tips and tricks: Put Google's most capable AI model to good use
Not sure what's up with Gemini? Here are the goods
Google Gemini has replaced Google Bard. Some have wondered if Gemini is another stepping stone until a better, more powerful AI model comes around to take its place. It happened with Bard and Duet AI, and now it's happening with Google Assistant. Despite some minor skepticism, many believe Google Gemini is a game changer for productivity on top-end Chromebooks and mobile applications.
Hugging Face is a platform for viewing, sharing, and showcasing machine learning models, datasets, and related work. It aims to make Neural Language Models (NLMs) accessible to anyone building applications powered by machine learning. Many popular AI and machine-learning models are accessible through Hugging Face, including LLaMA 2, an open source language model that Meta developed in partnership with Microsoft.
What is the difference between artificial intelligence and machine learning?
They are related to an extent but quite different
Artificial intelligence and machine learning are often used in the same context. They are related terms but have different purposes. AI has multiple applications across various industries, with the main idea of replicating human behaviors and intelligence in a manufactured way. Machine learning is the method used to train AI behind the scenes, allowing it to learn and carry out tasks independently. Even the most affordable Android smartphones have AI and machine learning elements built in, allowing for unique software-based features beyond the typical hardware limitations.
With Gemini, Google's inability to properly brand products is more apparent than ever
Is it Bard, Gemini, Assistant, or Now? I can't keep track
It's no secret Google is incredibly bad at naming its products, but it's also horrible at sticking with those names, and the recent switch from Bard to Gemini makes this all the more apparent. Why is Google so bad at branding? Clearly, that's a question for the ages when there are no brakes on the name change train.
Meta AI: What is it, who can use it, and how?
Learn about Meta AI and how you can use this free, open source artificial intelligence to chat, create images, and more
Meta is the company behind the largest social media networks in the world, including Facebook, Instagram, WhatsApp, and Messenger. It's also the metaverse company that makes the Quest VR headset and Ray-Ban Meta smart glasses. Given the tech giant's reach, it shouldn't be surprising that it's also a leading artificial intelligence company and the developer of Meta AI.
How Transfer learning improves and diversifies machine learning models
Transfer learning in AI mirrors human skill, using knowledge from one task to advance others
Artificial intelligence has begun to mirror a fundamental human skill: transfer learning. This approach is inspired by our cognitive abilities and leverages knowledge acquired in one task to advance in other domains. Just as humans use language to share and build upon their knowledge, artificial intelligence follows a similar path by applying insights from one dataset or problem to another. This article looks at what transfer learning is, how it works, why and when it should be used, and its benefits.
The year has only started and I'm already sick of hearing about AI
Marketing is predictably running the term AI straight into the ground
I didn't buy into the AI hype in late 2022. After all, I was still invested in the VR hype. Remember the metaverse? You know, the great new buzzword that replaced crypto and web3. Never mind, I was told the metaverse is dead. Long live AI! Microsoft slapped AI into everything the moment it partnered with ChatGPT, and Google quickly followed suit with Bard. Samsung, Intel, and even Apple are falling over themselves to create AI...stuff. It's only been a year, and I'm already sick of hearing about AI and how it's shipping in everything. The buzzword has worn out its welcome.
What is Google's AutoML Vision?
Google's AutoML Vision has helped train visual AI across industries: Here's how it works, what's replacing it, and more
Google has recently begun offering a large suite of AI tools to everyday businesses and ambitious software products that use Google platforms, perhaps from a capable Chromebook. One interesting example in the past few years is Google Cloud's AutoML Vision. This tool to create image analysis models may soon shut down for Vertex AI's rollout. However, you can still learn how it works and how to prepare data, which will be invaluable when using Google's similar future services. Let's look at the details.
A term that's casually thrown around these days is artificial intelligence (AI). AI continues to grow in popularity for multiple reasons. It can improve our lives by helping us in ways that go beyond hardware capabilities or increasing overall device efficiency. For example, you can grab one of the most affordable Android phones and benefit from many of the same AI features found on premium devices. In this guide, we mention certain aspects of AI and give examples of how it's used on our devices.
What are Google Cloud TPUs?
Google's aiming for the cloud-based AI creation sector: Google Cloud TPUs are helping it win
Google's foray into AI bots isn't limited to creations like the conversational Bard. Behind the scenes, the company has been working to support AI creation and management for years. That's led to some important developments, including TPUs or Tensor Processing Units.
What is Google Cloud Platform?
Google Cloud Platform is a suite of cloud computing services that enable developers to build, launch, and manage applications
Every tech giant seems to have a cloud platform. Still, if you asked someone what the Google Cloud was, they would probably have no idea. The Google Cloud Platform (GCP) isn't a collection of Google's most popular apps and software. They call that Google Workspace, which used to be G Suite.
What is Google BigQuery?
BigQuery plays a vital role in unlocking the potential of big data for businesses of all sizes
In the world of technology, being a big company means dealing with big data, and working with large amounts of data isn't possible with traditional data processing techniques. Think of billions of rows on a spreadsheet, and use cases ranging from terabytes to petabytes of data. In some cases, these data warehouses can be more than an exabyte.
You may have heard a lot about artificial intelligence (AI) and machine learning (ML) in recent years as the demand for each continues to rise. These two terms in the technology world have been tossed around for one specific reason: They take our device hardware beyond its physical limitations. For example, the best Android phones rely on an AI or ML model to achieve even more impressive photos from the camera. This guide discusses Google ML Kit and how it uses efficient on-device processing to improve our smartphone experience.
Google says machine learning is good for Maps, bad for scammers
New ML models have significantly improved scam detection in 2022
When it comes to finding your way around, Google Maps is one of the world's best apps to do it with. Barring Apple Maps, it's really got no competition. Its prominent positioning on Android devices as well as constant feature additions have played a big part of Maps' longevity. But what keeps the data on the app as accurate as it is are the user contributions that come in all the time — be it reviews or photos or speed trap spotters. But, as with any field of user-submitted content, it can be a scammers' playground full of shady links, non-existent businesses, or worse. The Google Maps team is now offering some details on what goes on behind the scenes to detect scammy content, usually before it even goes up.
Google Colaboratory, or "Colab" as most people call it, is a cloud-based Jupyter notebook environment. It runs in your web browser (you can even run it on your favorite Chromebook) and lets anyone with internet access experiment with machine learning and coding for artificial intelligence. You can write and execute Python code, share your code and edit it simultaneously with other team members, and document everything by combining it into a single notebook with rich text, charts, images, HTML, and LaTeX.
Line up now to talk to Google's definitely not sentient chatbot
An early chance to get in the good books of humankind’s future rulers
Big tech companies like Google and Microsoft are at the forefront of efforts to make human-computer interactions consumer-ready using technologies like natural language processing (NLP). One of Google’s most promising NLP models called LaMDA was recently in the news when a company researcher alleged the AI is sentient. If you've been curious what drove him to make such a bold claim, Google is now accepting registrations where you can sign up to interact with LaMDA yourself, through the AI Test Kitchen app announced earlier this year.
How Google's LaMDA AI works, and why it seems so much smarter than it is
A short history of Google's language-processing AI efforts
Fears surrounding the development of Artificial Intelligence are nothing new and have long been the basis of science fiction plots. But recently, a conversation between a researcher and a chatbot at Google has reinvigorated the discussion of what AI is and when and if something can be called “sentient.” That’s not a question I can answer (frankly, I’ve worked with honest-to-god biological human beings in the past that I’d have trouble labeling “sentient”), but I can tell you more about how Google’s LaMDA conversational AI works.