Connect with us

Tech

Experts don’t think AI is ready to be a ‘co-scientist’

Last month, Google announced the “AI co-scientist,” an AI the company said was designed to aid scientists in creating hypotheses and research plans. Google pitched it as a way to uncover new knowledge, but experts think it — and tools like it — fall well short of PR promises.

“This preliminary tool, while interesting, doesn’t seem likely to be seriously used,” Sarah Beery, a computer vision researcher at MIT, told TechCrunch. “I’m not sure that there is demand for this type of hypothesis-generation system from the scientific community.”

Google is the latest tech giant to advance the notion that AI will dramatically speed up scientific research someday, particularly in literature-dense areas such as biomedicine. In an essay earlier this year, OpenAI CEO Sam Altman said that “superintelligent” AI tools could “massively accelerate scientific discovery and innovation.” Similarly, Anthropic CEO Dario Amodei has boldly predicted that AI could help formulate cures for most cancers.

But many researchers don’t consider AI today to be especially useful in guiding the scientific process. Applications like Google’s AI co-scientist appear to be more hype than anything, they say, unsupported by empirical data.

For example, in its blog post describing the AI co-scientist, Google said the tool had already demonstrated potential in areas such as drug repurposing for acute myeloid leukemia, a type of blood cancer that affects bone marrow. Yet the results are so vague that “no legitimate scientist would take [them] seriously,” said Favia Dubyk, a pathologist affiliated with Northwest Medical Center-Tucson in Arizona.

“This could be used as a good starting point for researchers, but […] the lack of detail is worrisome and doesn’t lend me to trust it,” Dubyk told TechCrunch. “The lack of information provided makes it really hard to understand if this can truly be helpful.”

It’s not the first time Google has been criticized by the scientific community for trumpeting a supposed AI breakthrough without providing a means to reproduce the results.

In 2020, Google claimed one of its AI systems trained to detect breast tumors achieved better results than human radiologists. Researchers from Harvard and Stanford published a rebuttal in the journal Nature, saying the lack of detailed methods and code in Google’s research “undermine[d] its scientific value.”

Scientists have also chided Google for glossing over the limitations of its AI tools aimed at scientific disciplines such as materials engineering. In 2023, the company said around 40 “new materials” had been synthesized with the help of one of its AI systems, called GNoME. Yet, an outside analysis found not a single one of the materials was, in fact, net new.

“We won’t truly understand the strengths and limitations of tools like Google’s ‘co-scientist’ until they undergo rigorous, independent evaluation across diverse scientific disciplines,” Ashique KhudaBukhsh, an assistant professor of software engineering at Rochester Institute of Technology, told TechCrunch. “AI often performs well in controlled environments but may fail when applied at scale.”

Complex processes

Part of the challenge in developing AI tools to aid in scientific discovery is anticipating the untold number of confounding factors. AI might come in handy in areas where broad exploration is needed, like narrowing down a vast list of possibilities. But it’s less clear whether AI is capable of the kind of out-of-the-box problem-solving that leads to scientific breakthroughs.

“We’ve seen throughout history that some of the most important scientific advancements, like the development of mRNA vaccines, were driven by human intuition and perseverance in the face of skepticism,” KhudaBukhsh said. “AI, as it stands today, may not be well-suited to replicate that.”

Lana Sinapayen, an AI researcher at Sony Computer Science Laboratories in Japan, believes that tools such as Google’s AI co-scientist focus on the wrong kind of scientific legwork.

Sinapayen sees a genuine value in AI that could automate technically difficult or tedious tasks, like summarizing new academic literature or formatting work to fit a grant application’s requirements. But there isn’t much demand within the scientific community for an AI co-scientist that generates hypotheses, she says — a task from which many researchers derive intellectual fulfillment.

“For many scientists, myself included, generating hypotheses is the most fun part of the job,” Sinapayen told TechCrunch. “Why would I want to outsource my fun to a computer, and then be left with only the hard work to do myself? In general, many generative AI researchers seem to misunderstand why humans do what they do, and we end up with proposals for products that automate the very part that we get joy from.”

Beery noted that often the hardest step in the scientific process is designing and implementing the studies and analyses to verify or disprove a hypothesis — which isn’t necessarily within reach of current AI systems. AI can’t use physical tools to carry out experiments, of course, and it often performs worse on problems for which extremely limited data exists.

“Most science isn’t possible to do entirely virtually — there is frequently a significant component of the scientific process that is physical, like collecting new data and conducting experiments in the lab,” Beery said. “One big limitation of systems [like Google’s AI co-scientist] relative to the actual scientific process, which definitely limits its usability, is context about the lab and researcher using the system and their specific research goals, their past work, their skillset, and the resources they have access to.”

AI risks

AI’s technical shortcomings and risks — such as its tendency to hallucinate — also make scientists wary of endorsing it for serious work.

KhudaBukhsh fears AI tools could simply end up generating noise in the scientific literature, not elevating progress.

It’s already a problem. A recent study found that AI-fabricated “junk science” is flooding Google Scholar, Google’s free search engine for scholarly literature.

“AI-generated research, if not carefully monitored, could flood the scientific field with lower-quality or even misleading studies, overwhelming the peer-review process,” KhudaBukhsh said. “An overwhelmed peer-review process is already a challenge in fields like computer science, where top conferences have seen an exponential rise in submissions.”

Even well-designed studies could end up being tainted by misbehaving AI, Sinapayen said. While she likes the idea of a tool that could assist with literature review and synthesis, Sinapayen said she wouldn’t trust AI today to execute that work reliably.

“Those are things that various existing tools are claiming to do, but those are not jobs that I would personally leave up to current AI,” Sinapayen said, adding that she takes issue with the way many AI systems are trained and the amount of energy they consume, as well. “Even if all the ethical issues […] were solved, current AI is just not reliable enough for me to base my work on their output one way or another.”

source

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

Tech

Marc Lore says that AI will soon enable anyone open a restaurant

Marc Lore, the veteran e-commerce entrepreneur who sold his previous startups to Amazon and Walmart, has big plans to infuse AI into his current venture, Wonder.

The centerpiece of those plans is Wonder Create, an initiative that would let anyone — from food entrepreneurs to social media influencers — use AI to design and launch their own restaurant brand in under a minute. The virtual restaurant would then go live across Wonder’s growing network of tech-enabled kitchen locations, currently numbering 120 and expected to reach 400 next year.

Lore’s startup, a vertically integrated dining and delivery platform, has evolved from food trucks to fast casual restaurants with 10 to 20 seats. These are not normal restaurants, though; they are “programmable cooking platforms” capable of operating as 25 different types of restaurants based on cuisine, within their all-electric kitchens that are increasingly becoming robotic.

Speaking at The Wall Street Journal’s “Future of Everything” conference this week, Lore said these kitchens have a 700-ingredient library. The “restaurants” they house actually consist of many different brands that operate from within these locations.

In addition to a staff of up to 12 people in these kitchens, cooking tech, like conveyors and robotic arms, are involved in the cooking process. The company also just bought Spice Robotics, a maker of an automatic bowl-making machine previously used by Sweetgreen. Next year, it plans to offer an “infinite sauce machine” that can make bout 80% of all the sauces found in recipes on the internet today.

Wonder Create was announced earlier this year as a way for anyone to use Wonder’s software to launch their own restaurant brand and recipes.

Lore offered more details as how this would work by leveraging AI technology, describing the plan as something like a “Shopify front-end with an AI prompt.”

Techcrunch event

San Francisco, CA
|
October 13-15, 2026

“You type in what kind of restaurant you want to build. It builds the restaurant — AI does — in under a minute. It does the name, branding, description, pictures, pricing, health information, and all the recipes for your restaurant,” Lore explained during an interview at the WSJ event. The would-be restaurateur could then refine the prompt if changes were needed. When ready to go live, the restaurant would launch across all of Wonder’s locations.

The company currently has 120 of these “programmable cooking platforms” in operation, a number that’s expected to grow to 400 next year. As it adds robotics to the equation, the company won’t necessarily reduce headcount, Lore noted. Instead, it will increase the number of meals a kitchen can produce in a given period.

“We have about 7 million throughput capacity with 12 people,” he said. “We see a path to getting to 20 million throughput out of 2,500 square feet with just 12 people. The goal also is…I guess by 2035, to have 1,000 unique restaurants operating out of the 2,500 square feet,” Lore added.

The goal with these AI-created “restaurants” is to allow people to experiment with food in new ways. A restaurateur could test recipes to gauge customer reaction before adding dishes to his own brick-and-mortar locations, for example.

Lore sees other use cases for the platform, too, like letting influencers connect with their audience through their own “restaurant” brands without having to actually launch their own chains.

“It could be a mega-influencer, a micro-influencer — anyone that wants to monetize their following,” Lore said. “Or it could be a private trainer that wants to make specific bowls. It could be a not-for-profit. It could be Disney for [marketing] their new movie. Anybody can make a restaurant.”

Whether that many people actually want to is an open question. Ghost kitchens — a similar concept that promised to let brands sell food without owning a restaurant — had a rocky run in the early 2020s, with several high-profile operators scaling back or shutting down after struggling to build customer loyalty. Wonder’s added layer of automation and AI may address some of those pitfalls, but the model is still unproven at scale.

MrBeast Burger, a famous ghost kitchen experiments, vividly illustrated the challenge. The brand faced widespread complaints over inconsistent food quality — a consequence of relying on dozens of different contracted kitchens and staff. Wonder’s programmable, increasingly automated kitchens are designed to solve exactly that problem.

There are still limits to this idea, Lore admitted. Wonder’s team (including its robots) can’t do things like toss and stretch pizza dough or slice and roll sushi. Instead, Wonder’s focus is on simpler basics like burgers, chicken wings, fried chicken, and bowls.

The whole plan comes together with Lore’s other acquisitions — Grubhub for its 250 million-deliveries-per-year business and Blue Apron for its meal kit business. Now, Wonder is focused on buying restaurant brands, like New York City-based Blue Ribbon Fried Chicken, which it snapped up for $6.5 million in February.

“When you buy a brand — and you can buy a brand that has 10 locations, or even 50 locations — and then overnight put it in 1,000, there’s just an incredible arbitrage there,” Lore noted.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

source

Continue Reading

Tech

Peter Sarlin’s QuTwo reaches $380M valuation in angel round

QuTwo, the Finnish AI lab founded by former AMD Silo AI CEO Peter Sarlin, is now valued at €325 million (approximately $380 million) after raising a €25 million angel round ($29 million). It’s a sign of enduring tailwinds for AI, quantum computing, and sovereign tech, especially for Europe-made companies.

QuTwo’s name is a nod to quantum computing, but it hasn’t gone all-in on quantum. Its core product, QuTwo OS, is an orchestration layer that directs tasks to classical, quantum or hybrid architectures — with the idea that enterprise use cases are often best served by “quantum-inspired” computing, which uses classical chips to simulate quantum behavior on more reliable hardware.

Enterprise AI will be QuTwo’s bread and butter. The company already secured some $23 million in committed revenue thanks to design partnerships with the likes of retail giant Zalando, for which it helped develop AI assistants. “AI is the North Star that we will continue to aim for. Quantum is just a new type of compute,” said Sarlin, who is adamant that QuTwo is an AI company.

Momentum has been building around Europe-based AI labs, and several of them have become overnight unicorns. Just last week, former DeepMind researcher David Silver secured $1.1 billion for his new endeavor, Ineffable Intelligence. QuTwo’s valuation and round size are somewhat modest in comparison but will let it pursue its roadmap under less pressure.

According to Sarlin, who serves as QuTwo’s executive chairman, this was a decision he also made for his previous company, Silo AI, which AMD acquired for $665 million in 2024. “I had a lot of investors who would have wanted to pour a lot of money into making Silo into Europe’s OpenAI, but I didn’t believe in that play,” he told TechCrunch.

The main difference is that QuTwo wants the freedom to think long term, with a five- to ten-year horizon. “We are on a mission to build the globally leading AI company for the next paradigm, given that Europe did not succeed in building the AI company for this era,” Sarlin said.

It’s not that Sarlin is bearish on European AI, of which he is a prolific backer. Nor is he necessarily critical of extra-large rounds — he volunteered that he is also an investor in Yann LeCun’s Ami Labs, which raised $1.03 billion, and in British-American venture Recursive Superintelligence, which is rumored to be following the same path. But he didn’t see a billion-dollar round as the right fit for QuTwo — nor VC money, at least for now.

Techcrunch event

San Francisco, CA
|
October 13-15, 2026

Until recently, QuTwo was solely funded through Sarlin’s family office, PostScriptum, which also incubated NestAI, the other company where he serves as executive chairman. But whereas NestAI raised some $115 million in a funding round led by Finland’s sovereign fund and Nokia, QuTwo wasn’t seeking to raise external funding.

However, when the lab’s soft launch generated significant interest earlier this year, Sarlin decided he would say no to checks from VCs and strategic investors, but yes to an angel round in part due to the geopolitical moment Europe is currently navigating. 

With Europe increasingly looking to favor local alternatives to U.S. tech providers, there are tailwinds for AI made in Finland. But there is also investor appetite for a company that promises to facilitate more ambitious R&D initiatives in the fields where the region already has strong players, such as the automotive, life sciences and gaming sectors.

Conversely, Sarlin expects that QuTwo’s angel investors could open doors across Europe. There are definitely quite a few introductions he could request from this group, which includes Yuri Milner, Xavier Niel, Nico Rosberg, Dieter Schwarz and Niklas Zennström, and as well as many startup founders from Hugging Space, Legora, Miro, Skype, Supercell, Wolt, and more.

This will also support QuTwo’s growth. It recently expanded into Sweden, and has been hiring. According to Sarlin, some 50 quantum and AI scientists have joined the team, which includes two other second-time entrepreneurs: his former cofounder at Silo, Kaj-Mikael Björk; and Kuan Yen Tan, a cofounder at IQM, the Finnish quantum company that is set to go public.

QuTwo’s connection with IQM is also a reminder that the company believes we are about to enter the quantum era — it just can’t wait. “The question for repeat founders like [us] is how can we have even a larger impact. In the long term, it’s important for Europe that we build the AI company for the next paradigm out of Europe. But, in the short term, we can have a significant impact in driving ambitious R&D moon shots in Europe,” Sarlin said.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

source

Continue Reading

Tech

reMarkable’s new Paper Pure tablet goes back to basics with a monochrome screen

After exploring the bigger market for productivity tablets featuring color displays with the Paper Pro and the smaller Paper Pro Move, E Ink tablet maker reMarkable is returning to its roots with a new monochrome device called the Paper Pure.

The new, $399 Paper Pure succeeds the monochrome reMarkable 2 after six years, and comes with more powerful hardware as well as modern software features that make it competitive in today’s tablet market.

The Paper Pure has a 10.3-inch display when measured diagonally, the same as the reMarkable 2, but the new one is wider, which, the company says, makes it easier to take notes and read text. Notably, the resolution hasn’t changed between the two tablets, staying at 1872 x 1404 pixels with a pixel density of 226 PPI.

The tablet also comes with 32GB of storage, four times the amount you got on its predecessor, and is also about 40 grams lighter, weighing 360 grams.

Image Credits: reMarkableImage Credits:reMarkable

ReMarkable said the Paper Pure is 50% more responsive than the reMarkable 2, and offers 30% more battery life with its 3,820 mAh battery.

The company has added a slew of new features to the tablet to bring it up to par with modern productivity tools, including support for a web app. The Paper Pure lets you sync your calendar, as well as take and share notes for a particular meeting. And if you import documents from cloud storage services, the online sync service will automatically convert them into a notebook suited for reading and annotating on the tablet itself. The company said it also comes with better handwriting search capabilities.

The Paper Pure integrates with Slack, too, so you can convert handwritten notes into typed text that you can share. It also integrates with collaboration tool Miro, letting you share sketches and the like.

Techcrunch event

San Francisco, CA
|
October 13-15, 2026

The Norwegian company said it now plans to sunset production of the reMarkable 2, but will still offer software updates and support to existing customers.

The Paper Pure’s base model comes bundled with a stylus, and the costlier $449 version gets you a fancier stylus, dubbed Marker Plus, that includes an eraser function, plus a sleeve folio in various colors. Users can order the device starting today, and shipping is expected to start in early June.

The company said it has sold more than 3.5 million devices so far, and that it has 1.2 million subscribers for its Connect service, which offers unlimited cloud storage, exclusive templates, and the ability to create links to share notes or sketches.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

source

Continue Reading