On Wednesday, Intuit CEO Sasan Goodarzi announced in a letter to the company that it would be laying off 1,800 employeesabout 10 percent of its workforce of around 18,000while simultaneously planning to hire the same number of new workers as part of a major restructuring effort purportedly focused on AI.

"As Ive shared many times, the era of AI is one of the most significant technology shifts of our lifetime," wrote Goodarzi in a blog post on Intuit's website. "This is truly an extraordinary timeAI is igniting global innovation at an incredible pace, transforming every industry and company in ways that were unimaginable just a few years ago. Companies that arent prepared to take advantage of this AI revolution will fall behind and, over time, will no longer exist."

The CEO says Intuit is in a position of strength and that the layoffs are not cost-cutting related, but they allow the company to "allocate additional investments to our most critical areas to support our customers and drive growth." With new hires, the company expects its overall headcount to grow in its 2025 fiscal year.

Intuit's layoffs (which collectively qualify as a "mass layoff" under the WARN act) hit various departments within the company, including closing Intuit's offices in Edmonton, Canada, and Boise, Idaho, affecting over 250 employees. Approximately 1,050 employees will receive layoffs because they're "not meeting expectations," according to Goodarzi's letter. Intuit has also eliminated more than 300 roles across the company to "streamline" operations and shift resources toward AI, and the company plans to consolidate 80 tech roles to "sites where we are strategically growing our technology teams and capabilities," such as Atlanta, Bangalore, New York, Tel Aviv, and Toronto.

In turn, the company plans to accelerate investments in its AI-powered financial assistant, Intuit Assist, which provides AI-generated financial recommendations. The company also plans to hire new talent in engineering, product development, data science, and customer-facing roles, with a particular emphasis on AI expertise.

Despite Goodarzi's heavily AI-focused message, the restructuring at Intuit reveals a more complex picture. A closer look at the layoffs shows that many of the 1,800 job cuts stem from performance-based departures (such as the aforementioned 1,050). The restructuring also includes a 10 percent reduction in executive positions at the director level and above ("To continue increasing our velocity of decision making," Goodarzi says).

These numbers suggest that the reorganization may also serve as an opportunity for Intuit to trim its workforce of underperforming staff, using the AI hype cycle as a compelling backdrop for a broader house-cleaning effort.

But as far as CEOs are concerned, it's always a good time to talk about how they're embracing the latest, hottest thing in technology: "With the introduction of GenAI," Goodarzi wrote, "we are now delivering even more compelling customer experiences, increasing monetization potential, and driving efficiencies in how the work gets done within Intuit. But its just the beginning of the AI revolution."

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Intuits AI gamble: Mass layoff of 1,800 paired with hiring spree - Ars Technica

Enlarge / Whatever you do, don't ask the AI how many horizontal lines are in this image.

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In the provocatively titled pre-print paper "Vision language models are blind" (which has a PDF version that includes a dark sunglasses emoji in the title), researchers from Auburn University and the University of Alberta create eight simple visual acuity tests with objectively correct answers. These range from identifying how often two colored lines intersect to identifying which letter in a long word has been circled to counting how many nested shapes exist in an image (representative examples and results can be viewed on the research team's webpage).

If you can solve these kinds of puzzles, you may have better visual reasoning than state-of-the-art AIs.

The puzzles on the right are like something out of Highlights magazine.

A representative sample shows AI models failing at a task that most human children would find trivial.

Crucially, these tests are generated by custom code and don't rely on pre-existing images or tests that could be found on the public Internet, thereby "minimiz[ing] the chance that VLMs can solve by memorization," according to the researchers. The tests also "require minimal to zero world knowledge" beyond basic 2D shapes, making it difficult for the answer to be inferred from "textual question and choices alone" (which has been identified as an issue for some other visual AI benchmarks).

After running multiple tests across four different visual modelsGPT-4o, Gemini-1.5 Pro, Sonnet-3, and Sonnet-3.5the researchers found all four fell well short of the 100 percent accuracy you might expect for such simple visual analysis tasks (and which most sighted humans would have little trouble achieving). But the size of the AI underperformance varied greatly depending on the specific task. When asked to count the number of rows and columns in a blank grid, for instance, the best-performing model only gave an accurate answer less than 60 percent of the time. On the other hand, Gemini-1.5 Pro hit nearly 93 percent accuracy in identifying circled letters, approaching human-level performance.

For some reason, the models tend to incorrectly guess the "o" is circled a lot more often than all the other letters in this test.

The models performed perfectly in counting five interlocking circles, a pattern they might be familiar with from common images of the Olympic rings.

Do you have an easier time counting columns than rows in a grid? If so, you probably aren't an AI.

Even small changes to the tasks could also lead to huge changes in results. While all four tested models were able to correctly identify five overlapping hollow circles, the accuracy across all models dropped to well below 50 percent when six to nine circles were involved. The researchers hypothesize that this "suggests that VLMs are biased towards the well-known Olympic logo, which has 5 circles." In other cases, models occasionally hallucinated nonsensical answers, such as guessing "9," "n", or "" as the circled letter in the word "Subdermatoglyphic."

These gaps in VLM capabilities could come down to the inability of these systems to generalize beyond the kinds of content they are explicitly trained on. Yet when the researchers tried fine-tuning a model using specific images drawn from one of their tasks (the "are two circles touching?" test), that model showed only modest improvement, from 17 percent accuracy up to around 37 percent. "The loss values for all these experiments were very close to zero, indicating that the model overfits the training set but fails to generalize," the researchers write.

The researchers propose that the VLM capability gap may be related to the so-called "late fusion" of vision encoders onto pre-trained large language models. An "early fusion" training approach that integrates visual encoding alongside language training could lead to better results on these low-level tasks, the researchers suggest (without providing any sort of analysis of this question).

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Can you do better than top-level AI models on these basic vision tests? - Ars Technica

AI leaders are increasingly optimistic about the technologys potential in the health sector, especially when it comes to personalized bots that can comprehend and address individual health concerns.

OpenAI and Arianna Huffington are now jointly funding the development of an AI health coach through Thrive AI Health. In a Time magazine op-ed, OpenAI CEO Sam Altman and Huffington stated that the bot will be trained on the best peer-reviewed science alongside the personal biometric, lab, and other medical data youve chosen to share with it.

The company tapped DeCarlos Love, a formerGoogleexecutive who previously worked on Fitbit and other wearables, to be CEO. Thrive AI Health also established research partnerships with several academic institutions and medical centers likeStanford Medicine, the Rockefeller Neuroscience Institute atWest Virginia University, and the Alice L. Walton School of Medicine. (The Alice L. Walton Foundation is also a strategic investor in Thrive AI Health.)

AI-powered health coaches have become a popular fad: Fitbit is working on an AI chatbot coach, and Whoop added a ChatGPT-powered coach to give users more insight into their health metrics. In San Francisco, health data obsession is a staple. You wont go far without seeing someone wearing an Oura Ring or bragging about their sleep data from their Eight Sleep mattress.

Thrive AI Healths goal is to provide powerful insights to those who otherwise wouldnt have access like a single mother looking for quick meal ideas for her gluten-free child or an immunocompromised person in need of instant advice in between doctors appointments. Personally, Id use it to ask about every unusual headache, rather than relying on WebMDs often alarming diagnoses.

But one doesnt have to think hard to come up with reasons to be cautious: sharing your health data with anyone other than a primary care doctor could result in a leak of that information. Then theres the potential for the bot to provide dangerous or even fatal misinformation as well as the risk that quality care could be reduced to quick and flawed responses without human oversight.

The bot is still in its early stages, adopting an Atomic Habits approach. Its goal is to gently encourage small changes in five key areas of your life: sleep, nutrition, fitness, stress management, and social connection. By making minor adjustments, such as suggesting a 10-minute walk after picking up your child from school, Thrive AI Health aims to positively impact people with chronic conditions like heart disease. It doesnt claim to be ready to provide real diagnosis like a doctor would but instead aims to guide users into a healthier lifestyle.

AI is already greatly accelerating the rate of scientific progress in medicine offering breakthroughs in drug development, diagnoses, and increasing the rate of scientific progress around diseases like cancer, the op-ed read.

Advancing the medical system with AI could be tremendously beneficial for society, provided it actually works. While a bot that tells you to get more sleep isnt exactly on par with AI miracle cures, there has been some promising AI progress in the health sector, such as a study suggesting that a radiologist supported by a specialized AI tool can detect breast cancer from mammogram images as accurately as two radiologists. There are also AI-designed drugs currently in clinical trials, like one to treat fibrosis, and a team of M.I.T researchers used AI in 2020 to discover an antibiotic capable of killingE. coli.

For Altman and Huffington, the challenge will be building trust for a product that handles some of your most private information while navigating the limits of AIs power.

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OpenAI and Arianna Huffington are working together on an AI health coach - The Verge

The United States and several allies said Tuesday that they had seized control of a sophisticated Russian propaganda mill that used artificial intelligence to drive nearly a thousand covert accounts on the social network X.

Though governments have increasingly turned to AI in the past year to spread messages more widely and credibly, the takedown is unusual because the Western intelligence agencies traced it to an officer of the Russian FSB intelligence force and to a former senior editor at state-controlled publication RT, formerly called Russia Today, as explained in court filings.

In a strikingly detailed joint advisory, agencies in the United States, the Netherlands and Canada identified various software programs used to manage the network, including one named Meliorator, which created fictitious users known as souls in various countries. The FBI won a court order allowing it to seize two web domains that the operation had used to register the email addresses behind the accounts.

Todays actions represent a first in disrupting a Russian-sponsored Generative AI-enhanced social media bot farm, FBI Director Christopher A. Wray said in a statement. Russia intended to use this bot farm to disseminate AI-generated foreign disinformation, scaling their work with the assistance of AI to undermine our partners in Ukraine and influence geopolitical narratives favorable to the Russian government.

Automated accounts with more detailed biographies posted original content, while a supporting cast of more generic accounts liked and reshared those posts. Officials did not respond to questions about how many real users saw the posts and whether any spread the messages further, so it is unclear how effective the campaign was.

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The system evaded one of Xs techniques for verifying the authenticity of users by automatically copying one-time passcodes sent to the registered email addresses. References to Facebook and Instagram in the program code indicated that the operation intended to expand to those platforms, officials said.

The agencies recommended that social media companies improve their methods for catching covertly automated behavior.

X complied with a court order to furnish information on the accounts to the FBI, then deleted them. The company did not respond to questions from The Washington Post.

The Justice Department thanked X for its cooperation during the investigation, a sign of better communications between the government and the big social media companies after the Supreme Court upheld the right of officials to point out foreign influence operations.

John Scott-Railton, a researcher at the Canadian nonprofit the Citizen Lab, said the countries provided such detailed information about the inner workings of the botnet to help other investigators and companies know what to look for.

They dont think this problem is going anywhere, so they are sharing widely, Scott-Railton said.

The documents show that AIs large language models have helped Russian propagandists scale their operation and help with translation, he said. It also helps them avoid detection software that looks for repeated use of the same internet protocol addresses and other identifiers.

But many other systems are operating already, and they will get better as they adapt for what is getting detected and what is getting by, Scott-Railton said. This isnt even the tip of the iceberg, he said. This is the drip of the iceberg.

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U.S. and allies take down Russian bot farm powered by AI - The Washington Post

Intel could be giving its burgeoning foundry ambitions a much-needed shot in the arm, as the chip giants venture capital arm today revealed that its making a strategic investment in an Israel- and U.K.-based AI construction startup.

Intel Capital is leading a $15 million investment into Buildots, a company that uses AI and computer vision to create a digital twin of construction sites. The six-year-old company works with construction giants such as Pomerleau, NCC and Ledcor, serving them with 360-degree cameras to regularly capture on-site data to track project progress, identify bottlenecks and optimize workflows.

Buildots had previously raised around $106 million, with its most recent $60 million tranche coming two years ago.

While Intel Capital has plowed billions into AI startups through the years, its decision to buy a stake in Buildots is particularly notable right now, coming as its parent company doubles down on efforts to increase its own manufacturing capacity while trying to keep costs in check.

A few years back, Intel revealed plans to invest$20 billion in two new fabrication facilities (or fabs) at its Ocotillo campus in Arizona. At the same time, Intel also launched a new foundry business recently rebranded as Intel Foundry with a view toward manufacturing chips designed by other companies.

These two new Arizona factories, dubbed Fab 52 and Fab 62, are expected to hit completion by early 2025. But they are among a number of massive construction projects Intel has on the go around the world right now, including plans for two new plants in Ohio that could cost up to $28 billion. These were originally expected to start bearing fruit in 2025, though the company recently announced it would have to delay these plans by a year, citing market challenges.

So Intel is something of a construction powerhouse, with its current spend across four U.S. states alone pegged at around $100 billion spanning new builds and refurbs. Pressure is mounting, though, as its recent earnings showed that its Foundry business losses widened last year, while the company faced another setback when regulatory hurdles forced it to pull the plug on a $5.4 billion merger with contract chipmaker Tower Semiconductor. (The pair instead struck a commercial partnership that will see Intel provide foundry services to Tower as part of a $300 million investment.)

To help with these various manufacturing endeavors, Intel is also set to receive $8.5 billion in government funding as part of U.S. plans to bring more chip manufacturing in-house, as it were.

However, one of the best ways to cut costs is to improve efficiencies, which is where Buildots could help. Just recently, the company launched a new AI-powered delay forecast feature that claims to predict when delays might occur to help project managers take preemptive action.

Buildots said at the time of the launch that during beta testing on major construction sites, the delay forecast feature was able to reduce delay times by up to 50% in some scenarios.

Historically, the construction industry was always deemed to have been slower than most to embrace digitization. This is in part due to the complexity and unique nature of each project, as well as the multi-stakeholder coordination required, spanning architects, contractors, engineers, suppliers, regulators and more. But there are signs that this is changing, particularly with the advent of AI, which while unable to build a tower block is showing some promise in terms of helping to reduce timelines on the operational side.

Neither Intel nor Buildots would directly confirm whether they are already working together, though Buildots has alluded to this on social media in the past with references to collaborations with industry giants like Intel.

In a statement issued to TechCrunch, Intel Capitals investment director Lisa Cohen said that Intels own experiences in the construction realm have helped it understand the need to drive efficiencies through technology.

Intels first-hand experience building some of the largest and most complex construction projects in the world has certainly played a role in leading us to appreciate the tremendous potential AI technology in general, and Buildots specifically, holds in terms of revolutionizing construction process management and driving efficiency to new levels, Cohen said.

As a result of the investment, Cohen will now be joining Buildots board of directors. Other investors in the round include Israels OG Tech Partners among other unnamed previous investors.

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Intel Capital backs AI construction startup that could boost Intels own manufacturing prospects - TechCrunch