GenAI Weekly — Edition 34
Your Weekly Dose of Gen AI: News, Trends, and Breakthroughs
Stay at the forefront of the Gen AI revolution with Gen AI Weekly! Each week, we curate the most noteworthy news, insights, and breakthroughs in the field, equipping you with the knowledge you need to stay ahead of the curve.
OpenAI introduces ChatGPT Search
ChatGPT can now search the web in a much better way than before. You can get fast, timely answers with links to relevant web sources, which you would have previously needed to go to a search engine for. This blends the benefits of a natural language interface with the value of up-to-date sports scores, news, stock quotes, and more.
ChatGPT will choose to search the web based on what you ask, or you can manually choose to search by clicking the web search icon.
Search will be available at chatgpt.com (opens in a new window) , as well as on our desktop and mobile apps . All ChatGPT Plus and Team users, as well as SearchGPT waitlist users, will have access today. Enterprise and Edu users will get access in the next few weeks. We’ll roll out to all Free users over the coming months.
GitHub Copilot will support models from Anthropic, Google, and OpenAI
GitHub is going multi-model for its Copilot code completion and programming tool. Developers will soon be able to choose models from Anthropic, Google, and OpenAI for GitHub Copilot. GitHub is also announcing Spark, an AI tool for building web apps, and updates to GitHub Copilot in VS Code, Copilot for Xcode, and more at its GitHub Universe conference today.
GitHub Copilot users on the web or VS Code can select Claude 3.5, with Gemini 1.5 Pro in the coming weeks. OpenAI’s GPT-4o, o1-preview, and o1-mini models will also be available in GitHub Copilot soon. Developers will be able to toggle between models during a conversation with Copilot Chat to find the model that’s best for a particular task.
“There is no one model to rule every scenario, and developers expect the agency to build with the models that work best for them,” says GitHub CEO Thomas Dohmke. “It is clear the next phase of AI code generation will not only be defined by multi-model functionality, but by multi-model choice.”
Question is: if LLMs can be replaced with one another, does it mean they’re becoming commodity?
GitHub Spark lets you build web apps in plain English
When GitHub Copilot launched and started autocompleting lines of code — and, later, entire code snippets — the question many people were asking was: How long until we can just describe an app in natural language and Copilot will build it for us? We’ve seen quite a few experiments in this arena in recent months, but now, GitHub itself is throwing its weight behind this idea with the announcement of GitHub Spark at the company’s annual GitHub Universe conference in San Francisco.
Spark, which is officially an experiment the company is launching out of its GitHub Next labs, allows you to quickly build a small web app using nothing but natural language. Experienced developers can still see and edit the code — and underneath it all is a GitHub repository, GitHub Actions, and Microsoft’s Azure CosmosDB as the default database for applications that need one — but that’s optional. Ideally, you’ll be able to use a chat-like experience to create a prototype and then refine it in subsequent steps.
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Users can easily share their Sparks with customized access controls. What’s maybe even more interesting, though, is that those users can also take the shared code and build upon it themselves.
Developers who want to take these applications even further can look at the code at any time — and edit it if there’s an issue, which Dohmke acknowledges could happen. AI isn’t perfect, after all. “You can, of course, look into the code base,” he said. “So if you have an understanding of the code base, you can also look at the code directly and modify that, which is often helpful when the AI makes a mistake — which does happen.”
My take on this: The castle of software development is facing a full-on attack after a new weapon has appeared.
Google CEO says more than a quarter of the company's new code is created by AI
More than a quarter of new code created at Google is generated by AI, said CEO Sundar Pichai on Tuesday during the company's Q3 earnings call.
Pichai said using AI for coding was "boosting productivity and efficiency" within Google. After the code is generated, it is then checked and reviewed by employees, he added.
"This helps our engineers do more and move faster," said Pichai. "I'm energized by our progress and the opportunities ahead, and we continue to be laser focused on building great products."
My take on this: This is the future, like it or not.
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Report: Google preps ‘Jarvis’ AI agent that works in Chrome
According to The Information , Google is “developing artificial intelligence that takes over a person’s web browser to complete tasks such as gathering research, purchasing a product or booking a flight.”?
“Project Jarvis” — in a nod to J.A.R.V.I.S. in Iron Man — would operate in Google Chrome and is a consumer-facing (rather than enterprise) feature to “automate everyday, web-based tasks.” The article doesn’t specify whether this would be for mobile or desktop.
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Given a command/action, Jarvis works by taking “frequent screenshots of what’s on their computer screen, and interpreting the shots before taking actions like clicking on a button or typing into a text field.” Today’s report says Jarvis “operates relatively slowly because the model needs to think for a few seconds before taking each action.” As such, this is most likely not working on-device yet and still requires the cloud.
Jarvis is said to be powered by Gemini 2.0 and might be previewed “as early as December,” thus confirming another rumor yesterday . After that, Jarvis might be made available to early testers, so a launch does not seem imminent. It makes sense for Google to have a flagship example of something powered by Gemini 2.0. It has done that for past model launches, and Jarvis seems much more tangible.
My take on this: Welcome to the new Browser Wars 2.0.
Not just ChatGPT anymore: Perplexity and Anthropic’s Claude get desktop apps
There's a lot going on in the world of Mac apps for popular AI services. In the past week, Anthropic has released a desktop app for its popular Claude chatbot, and Perplexity launched a native app for its AI-driven search service.
On top of that, OpenAI updated its ChatGPT Mac app with support for its flashy advanced voice feature.
Like the ChatGPT app that debuted several weeks ago, the Perplexity app adds a keyboard shortcut that allows you to enter a query from anywhere on your desktop. You can use the app to ask follow-up questions and carry on a conversation about what it finds.
It's free to download and use, but Perplexity offers subscriptions for major users.
Gartner predicts AI agents will transform work, but disillusionment is growing
Very quickly, the topic of AI agents has moved from ambiguous concepts to reality. Enterprises will soon be able to deploy fleets of AI workers to automate and supplement — and yes, in some cases supplant — human talent.?
“Autonomous agents are one of the hottest topics and perhaps one of the most hyped topics in gen AI today,” Gartner distinguished VP analyst Arun Chandrasekaran said at the Gartner Symposium/Xpo this past week.?
However, while autonomous agents are trending on the consulting firm’s new generative AI hype cycle, he emphasized that “we’re in the super super early stage of agents. It’s one of the key research goals of AI companies and research labs in the long run.”?
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At the same time, some enterprise leaders say AI hasn’t lived up to the hype. Gen AI is beginning to slide into the trough of disillusionment (when technology fails to meet expectations), said Chandrasekaran. But this is “inevitable in the near term.”
There are a few fundamental reasons for this, he explained. First, VCs have funded “an enormous amount of startups” — but they have still grossly underestimated the amount of money startups need to be successful. Also, many startups have “very flimsy competitive moats,” essentially serving as a wrapper on top of a model that doesn’t offer much differentiation.
Also, “the fight for talent is real” — consider the acqui-hiring models — and enterprises underestimate the amount of change management. Buyers are also increasingly raising questions about business value (and how to track it).
There are also concerns about hallucination and explainability, and there’s more to be done to make models more reliable and predictable. “We are not living in a technology bubble today,” said Chandrasekaran. “The technologies are sufficiently advancing. But they’re not advancing fast enough to keep up with the lofty expectations enterprise leaders have today.”
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