Set to arrive in Wix’s app builder tool this week, the capability guides users through a chatbot-like interface to understand the goals, intent and aesthetic of their app.
But reviews of Wix’s AI site builder aren’t exactly glowing, with early adopters reporting bugs and generic-looking finished products.
So — given that the under-the-hood tech is similar, outside a few upgraded generative AI models — why should people expect Wix’s AI app builder to be any better?
Image Credits: WixAbrahami admitted that the AI app builder — like all generative AI tools — might make mistakes.
On Fiverr, a cursory search yields a long list of highly-rated app developers, some of whom charge around the same price as a subscription to Wix’s AI app builder.
With the launch of TC’s AI newsletter, we’re sunsetting This Week in AI, the semiregular column previously known as Perceptron.
But you’ll find all the analysis we brought to This Week in AI and more, including a spotlight on noteworthy new AI models, right here.
The group published an open letter on Tuesday calling for leading AI companies, including OpenAI, to establish greater transparency and more protections for whistleblowers.
(Reward models are specialized models to evaluate the outputs of AI models, in this case math-related outputs from GPT-4.)
Should generative AI replace most knowledge workers within three years (which seems unrealistic to me given AI’s many unsolved technical problems), economic collapse could well ensue.
Every company, large or small, needs to choose software, and the bigger the company, the more complex the exercise.
Some have internal tools and processes to help narrow down the list of possible vendors and eventually make a selection.
“Taloflow replaces homegrown technology and software selection processes that can last weeks or months,” the startup’s CEO and co-founder, Louis-Victor Jadavji, told TechCrunch.
“Unlike Gartner or G2, which offer mostly generic insights, Taloflow creates tailored reports for specific use cases,” he said.
Taloflow has built large language models that sift through publicly available information and speed up the time and cost of generating the base reports.
The company on Wednesday introduced a beta of what it’s calling ‘AI teammates,’ in a bid to help move work inside an organization.
“We believe that the future of work is humans not just working with humans, but humans also working with AI,” Costello told TechCrunch.
“The work graph enables us to tell AI not just how work happens, but how work happens in this specific instance.
So when we embed AI teammates into a particular workflow, they’re given a specific job to do.
“We have found that we’re able to embed AI teammates to remove a lot of administrative work and tracking work within these systems very quickly, with high degrees of success.
Hoop, a productivity startup founded by a group of early Trello employees, wants to use AI to help you automatically generate and track your to-do list.
Image Credits: HoopThe core idea behind Hoop is that it will use AI to automatically capture potential tasks from Google Meet and Slack meetings and Slack messages (with other platforms coming later, starting with email) and pull those into the Hoop to-do list.
Currently, Hoop is a bit of a single-player experience, but Garber tells me that the company plans to add more team features in the future.
“We are really, really focused on making [Hoop] as useful for the individual as possible before we expand to teams, but it’s a very natural thing for us to do,” Garber said.
And while Hoop right now mostly looks like a standard to-do list, the company plans to add different views over time as well.
eBay’s newest AI feature allows sellers to replace image backgrounds with AI-generated backdrops.
eBay’s background enhancement tool could benefit sellers who lack the equipment or skills to take professional-looking or high-quality photos.
It may also improve on eBay’s previous offering, which used computer vision technology to give listing photos a simple, white background.
The new AI feature is powered by the open-source model Stable Diffusion.
The latest announcement comes a year after eBay introduced an AI feature that generates titles and descriptions for a product listing.
Google’s newest startup program, announced on Wednesday, aims to bring AI technology to the public sector.
The newly launched “Google for Startups AI Academy: American Infrastructure” will offer participants hands-on training from AI experts and other support for companies solving problems in areas like agriculture, energy, education, public safety, healthcare, telecommunications, transportation, urban development, and more.
Over the course of twelve weeks, startups participating in the equity-free program will be guided by an AI curriculum developed by Google’s People + AI Research (PAIR) team and will participate in advanced sales and go-to-market workshops.
They’ll also be able to access industry connections and, of course, tap into Google’s AI tools as they build.
While much focus is on the AI companies building the models, tools, and interfaces for working with AI, a focus on real-world applications of the technology could impact communities at the local, state, and national levels, Google believes.
The weather’s getting hotter — but not quite as hot as the generative AI space, which saw a slew of new models released this week, including Meta’s Llama 3.
In other AI news, Hyundai-owned robotics company Boston Dynamics unveiled an electric-powered humanoid follow-up to its long-running Atlas robot, which it recently retired.
And Rebecca and Sean report on layoffs at Tesla , which they say hit high performers and gutted some departments.
AnalysisGoogle Cloud bets on generative AI: Ron writes about how Google Cloud is investing heavily in generative AI, as evidenced by the string of announcements during Google’s Cloud Next conference earlier in the month.
Generative AI in health: Generative AI is coming for healthcare — but not everyone’s thrilled.
Why vector databases are having a moment as the AI hype cycle peaks GenAI spurs demand for vector search startups, but database giants are also taking noteVector databases are all the rage, judging by the number of startups entering the space and the investors ponying up for a piece of the pie.
“Working with visual search and robotics at Amazon was when I really looked at vector search — I was thinking about new ways to do product discovery, and that very quickly converged on vector search,” Clark told TechCrunch.
“I think the same is likely to happen with vector databases,” Zaitsev told TechCrunch.
“Our pitch is, ‘we do advanced vector search in the best way possible.’ It is all about specialization.
At some point, users will face limitations if vector search is a critical component of your solution.”
Allison Cohen is the senior applied AI projects manager at Mila, a Quebec-based community of more than 1,200 researchers specializing in AI and machine learning.
One of the projects I managed involved building a dataset containing instances of subtle and overt expressions of bias against women.
I learned firsthand why this process is fundamental to building responsible applications, and also why it’s not done enough — it’s hard work!
What advice would you give to women seeking to enter the AI field?
How can investors better push for responsible AI?
