com’s parent company, Automattic, last year, is now available to users on Android devices.
Mesh, the relationship manager and personal CRM acquired by WordPress.com’s parent company, Automattic, last year, is now available to users on Android devices. The software allows users to privately visualize and keep track of the people in their personal and professional networks, add notes to people’s contact information, and be reminded when to reach out. On Android, the company customized Mesh’s app to work with key platform features, like split-screen and pop-up views. This allows users to access Mesh while working in other apps, like messages or email. It also supports keyboard shortcuts for foldables and tablets, in-app search, home screen widgets (with Material You colors that match your Android’s wallpaper), and real-time sync across devices. Image Credits:Mesh The company’s broader plans for Mesh could eventually see it tied more closely to Automattic’s all-in-one messaging app, Beeper, which offers a way to connect with people across platforms, including through WhatsApp, Instagram, Signal, Messenger, X, LinkedIn, Slack, Discord, Google Messages, and more. Already, Mesh and Beeper interoperate to some extent, as Mesh users can draft a text to someone in Beeper or click deep links in the app to visit a Mesh user’s profile. In time, the company wants to add additional AI features that will make users of both products more productive in terms of managing their personal relationships. “We’re thinking a lot about how can AI help you be a better friend and have better work and personal relationships?,” Mesh co-founder Zachary Hamed told TechCrunch in an interview earlier this spring. “We have users who have ten-, twenty-, or fifty-thousand connections across multiple social media apps, across their work products. It’s an impossible task to think and be conscientious with you, with each of those people, by yourself,” he noted. Image Credits:Mesh Today, Mesh’s Nexus AI is in early access, offering a way to use AI to navigate your network. That means users can ask questions like who they know at a particular company or who lives in a certain city, or who has expertise in a particular topic. The company is also experimenting with using AI technology to provide a voice-based, hands-free experience and an improved business card scanning feature. Importantly, personal information stored in Mesh isn’t shared or used for ad targeting, the company says, as the product is supported by subscriptions. (It’s free for up to 1,000 contacts, then has higher tiers for unlimited contacts and other features.) In time, Mesh may consider a bundled subscription with Beeper or other Automattic products, but has nothing to announce on that front at this time. Currently, the majority of Mesh’s customers, or around 70%, are using the app for some type of business purpose. Mesh co-founder Matthew Achariam says Mesh’s sweet spot is executives running bigger teams or those who have a tight network to stay in touch with. However, the company still thinks about the consumer use case, he notes. “The beauty of [serving business users] is that the same things they’re using apply to every individual consumer. So every feature that we think about has to apply to both,” he says. Mesh (formerly Clay) for Android will roll out to Google Play for phones, tablets, and foldables as a free download with in-app purchases. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence. Sarah has worked as a reporter for TechCrunch since August 2011. She joined the company after having previously spent over three years at ReadWriteWeb. Prior to her work as a reporter, Sarah worked in I.T. across a number of industries, including banking, retail and software. You can contact or verify outreach from Sarah by emailing or via encrypted message at sarahperez.01 on Signal. View Bio
Jeff Dean, one of the longest-serving and most influential executives at Google, is stepping down from the search giant to launch his own AI startup. Coming with him as co-founders are several other top researchers at the company, including Sanjay Ghemawat, a top engineer and senior fellow at Google, Quoc Le, a key AI researcher and founding member of Google Brain, and Oriol Vinyals, a senior research scientist at Google DeepMind. Dean reportedly plans to serve as CEO. Together, the group is starting Discovery Loop, a public benefit corporation that seeks to use AI to turbo-charge scientific research. Discovery Loop says it plans to use high-octane algorithms to initiate and iterate thousands of experiments simultaneously, with the goal of partially automating the research process and expanding the scale at which experimentation can be conducted. The startup is also interested in using AI to help create more powerful AI (a process known as recursive self-improvement), which would cut human iteration out of the loop entirely. “While science and engineering have tremendously advanced society over past centuries, progress has traditionally relied on slow, sequential human iterations, creating a significant bottleneck,” the company said in a press release. “Discovery Loop is developing advanced AI systems that leverage massive computational scale to fundamentally transform the speed and efficiency of innovation by automating complete experimental loops.” Using AI to accelerate scientific discovery has been a key interest of the science and tech communities for many years, but until recently, it remained a largely experimental field with limited commercial application. The company has received financial support from a number of different sources, including Google’s parent company Alphabet. The initial funding round is being co-led by Radical Ventures and Khosla Ventures, the company announced Wednesday. Kleiner Perkins, Lightspeed, and Doerr Capital also participated. “The next great frontier for AI is to go beyond answering questions and to begin making discoveries,” the founding team said in a joint statement. “By fundamentally accelerating how engineering and scientific discovery are conducted, we can deliver the benefits of transformative technologies to the world far sooner.” Dean has worked at Google since 1999 and was Google’s 30th employee. Over the years, he has contributed to Google search’s core infrastructure, including its crawling and indexing system, and its query-serving system. He has also had a significant impact on Google Gemini’s multimodal models, and played a leading role in the company’s early AI research. “We think there is opportunity for AI to more fully automate what has traditionally been a very human-intensive experimental loop,” Dean told the New York Times. “You will get both a higher quantity and a higher quality of experiments, and that will lead to scientific breakthroughs and advances.” When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence. Lucas is a senior writer at TechCrunch, where he covers artificial intelligence, consumer tech, and startups. He previously covered AI and cybersecurity at Gizmodo. You can contact Lucas by emailing lucas.ropek@techcrunch.com. View Bio
Lucid Motors was just months away from releasing its most affordable electric vehicle yet, a crossover SUV called the Cosmos that was supposed to start under $50,000. But this week, the company pushed the release of the Cosmos back by almost a full year to the second half of 2027, part of an effort by its new CEO to avoid the quality problems that Lucid has suffered with its existing EVs. It’s the latest setback for the company, which has struggled to find more than a niche customer base for its expensive, but technologically impressive, vehicles. And it’s one that CEO Silvio Napoli presented as necessary for the company to survive. “While there is no question that Lucid brought leading innovations and outstanding products to the market, we have disappointed on several fronts, and for far too long,” Napoli said this week. “We have not executed consistently. We missed commitments, launched products before they were ready, underinvested in service, responded too slowly to quality issues, and allowed complexity to slow decisions down.” Napoli’s sober assessment, which he offered on the company’s second-quarter earnings call, helps explain why he has taken an axe to the company’s leadership structure and overall workforce. Multiple executives have left since he officially took over on June 1, including Senior Vice President of Finance Gagan Dhingra, whose departure was disclosed at the bottom of the company’s second-quarter financial filing with the Securities and Exchange Commission (SEC) on Tuesday. Napoli has replaced those outgoing executives with an entirely new C-suite as he embarks on a cost-cutting mission aimed at achieving $1.4 billion in savings by the end of this year. Napoli also cut 18% of Lucid’s overall workforce in June, following a 12% layoff earlier this year before he came on board. He canceled a second shift at Lucid’s factory in Arizona, citing lower demand for the company’s EVs — including its Gravity SUV, which has not taken off as the company expected despite being a more popular form factor than its first EV, the Air sedan. The Cosmos had been seen by some as a light at the end of the tunnel. It’s supposed to be the first of several cars built on Lucid’s next-generation “mid-size” EV platform, which is smaller and cheaper to build. The much lower price tag is supposed to help Lucid attract more customers and reach higher sales volumes. But Napoli seems worried that the upside of getting the Cosmos EV to market could be negated if Lucid doesn’t get the launch right. Though he didn’t explicitly name the SUV, Napoli said on the call this week that he delayed Cosmos because he doesn’t want to run into the same kind of problems Lucid has had with previous vehicles, clearly referring to the Gravity. The company has struggled with build quality and software issues on the Gravity. Things got so bad at one point that Napoli’s predecessor, interim CEO Marc Winterhoff, apologized to Lucid owners. “We will not repeat the mistakes of the past by bringing a product to market before it is ready,” Napoli said on the call. The decision to delay Cosmos will likely disappoint some customers who were hoping to buy one by the end of this year. But the delay, combined with the decision to lower production in Arizona, is also affecting Lucid’s supply base. In the company’s quarterly filing with the SEC, it wrote that “lower production volumes or demand, or reductions in our projected production volumes, have negatively affected, and could continue to adversely affect, our relationships with existing suppliers, who may seek to increase pricing, assert contractual or other claims, or otherwise fail to perform or comply with contractual obligations.” Napoli’s big “reset” of Lucid Motors means the company now has to tread water for another year until the Cosmos EV goes into production. The company said Tuesday that it has “sufficient liquidity runway well into 2027.” But it also warned Wall Street analysts that it is g
Reddit on Wednesday announced a series of changes to its infrastructure and tools, designed to make it easier for people to participate on its site, protect against scraping and spam, and aid in the moderation of its online communities. In addition to providing a new suite of moderation tools, the company said it’s working on more advanced abuse prevention systems that could eventually help communities move away from using things like account age and “karma” to determine who’s allowed to post. Karma, Reddit’s digital reputation system, allows users to raise their score by posting and commenting helpful, friendly, or funny responses that lead to upvotes. Originally designed to weed out spam, bots, and trolls, many communities came to rely on karma and other account-age restrictions that make it difficult for legitimate newcomers to participate in their communities. Reddit says it now wants to shift to stronger, built-in abuse prevention systems to do more of the moderation work, so communities can be more open to new users. Reddit didn’t say karma would go away entirely with these coming changes, but it did suggest that its importance could dwindle in the future. “This will make it easier for genuine new users to participate and easier for mods to welcome them with confidence,” Reddit’s announcement stated. Related to this, the company said it’s expanding the test of its new suite of AI-powered moderation tools, the Rules Hub, which helps moderators by choosing when to automatically enforce certain community rules and what action should be taken when doing so. Initially used by 700-plus communities, Reddit says that all new communities can now test the tool. Later this year, the tool will be widely available to all communities, both new and existing. With Rules Hub, Reddit uses large language models (LLMs) to determine whether a post or comment matches the intent of a rule, which the company says allows it to “better handle nuance,” natural language, and edge cases. Reddit also expanded the capabilities of other tools, including one that helps moderators inform users about their community’s rules when posting and commenting, and another that helps members set their flair — a custom tag users append to their name that only appears in the community they’re posting in. “Today, new users can encounter invisible barriers like account age and karma thresholds, unclear removals, and poor community discovery,” Reddit explained. “We want new users around the world to be able to easily find relevant communities, understand their rules and norms, and make useful contributions.” The company also said it would make changes to its legacy desktop site, Old Reddit, by shifting its moderator workflows to its new stack and migrating other critical bots. On Reddit’s second-quarter earnings calls with investors last week, company executives stressed that one of Reddit’s near-term goals was to convert its half-billion weekly active users to daily users through product updates. The company had crushed earnings with revenue of $805 million and earnings per share of $1.25, above estimates, but still saw its stock sink because of what Reddit CEO Steve Huffman described as “choppy” search referral traffic. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence. Sarah has worked as a reporter for TechCrunch since August 2011. She joined the company after having previously spent over three years at ReadWriteWeb. Prior to her work as a reporter, Sarah worked in I.T. across a number of industries, including banking, retail and software. You can contact or verify outreach from Sarah by emailing sarahp@techcrunch.com or via encrypted message at sarahperez.01 on Signal. View Bio
E-commerce software maker Shopify seems to be benefiting handily from people using AI to search. On the company’s second-quarter earnings call, Shopify President Harley Finkelstein said AI has become a “complement to search, rather than a substitute for it,” and had particularly benefited the long tail of e-commerce, including the smaller merchants that make up the majority of its customer base. Indeed, the company credited its earnings beat and soaring revenue to AI search, at least partly. This is quite different from how AI is impacting online publishing, where AI summaries have led to a measurable drop in click-through rates, which lowers traffic and consequently eats into advertising revenues. Instead, Shopify believes that AI is a boon to its business. The company noted that AI-driven traffic and orders to Shopify stores had tripled year-over-year in the second quarter. And, this was not a result of AI taking share from search. “In fact, search remains one of our largest sources of buyer traffic to our merchants, and it’s still growing,” Finkelstein told analysts on the call. “Traditional search sessions are up 1.3x over the past two years, holding roughly a third of all storefront sessions.” The e-commerce platform reported strong results in the quarter, with revenue rising 36% to $3.6 billion from a year earlier, outstripping Wall Street’s forecast of $3.4 billion. Gross operating profit rose 31% to $1.71 billion, also ahead of analysts’ expectations of $1.63 billion. The company went into further detail about why AI search was working for its business. “While search engines rank by popularity against a handful of keywords, AI agents make multiple calls into Shopify’s catalog, working with richer structured data to match products with the buyer’s specific intent, rather than just keywords,” Finkelstein explained. “When a buyer asks an AI assistant for the best car seat that fits three across a sedan, traditional search focuses on the keyword ‘car seat.’ An agent, however, understands the actual need, the dimensions, the vehicle type, and the fact that they need three. It searches across all of those constraints at once to find the product that actually works, not just the one that ranks highest,” he said. In other words, AI’s capability to search across many dimensions to find the best product for users is resulting in better conversions for merchants. “Buyers’ shopping journeys are being compressed as half of all AI-referred sessions are landing directly on a product description page. That is 2.5 times more than what we see with traditional search,” Finkelstein added. Plus, the company said 75% of AI-attributed purchases in Q2 happened outside the top 100 categories, or what Shopify called its “sweet spot.” In addition, the company suggested Shopify stands to benefit from AI playing a larger role in transactions thanks to its trusted checkout experience. The company pointed out that it’s also working with AI tools and agents, having built connectors to Claude, ChatGPT, Perplexity, Manus, Replit and Vercel, as well as vibe-coding platforms like Lovable that let merchants build on Shopify however they choose. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence. Sarah has worked as a reporter for TechCrunch since August 2011. She joined the company after having previously spent over three years at ReadWriteWeb. Prior to her work as a reporter, Sarah worked in I.T. across a number of industries, including banking, retail and software. You can contact or verify outreach from Sarah by emailing sarahp@techcrunch.com or via encrypted message at sarahperez.01 on Signal. View Bio
Lucid Motors said Tuesday that its “operational reset” will focus on $1.4 billion in cash reductions along with three other “must win” and potential money-making priorities that include robotaxis, its factory in Saudi Arabia, and launching a mid-sized electric vehicle. The turnaround plan, led by its new CEO Silvio Napoli, aims to pull Lucid out of its spiral of growing EV inventory and unchecked spending. To reach that $1.4 billion in cash savings, Lucid said it will reduce capital expenditures by $500 million and projected savings of between $600 million and $800 million in inventory, according to its second-quarter earnings statement. The company said it will also reduce operating expenses by $200 million. The effort, if successful, will provide sufficient liquidity runway well into 2027, Napoli said during Tuesday’s earnings call with investors. Napoli didn’t mince words during his first quarterly earnings call as CEO. “The way we operate has to change,” he said. “While there is no question that Lucid brought leading innovations and outstanding products to the market, we have disappointed on several fronts, and for far too long. We have not executed consistently, we miss commitments, launched products before they were ready, underinvested in service, responded too slowly to quality issues, and allowed complexity to slow decisions down.” Napoli has already set some of this plan in motion. The company has shaken up its leadership ranks and hired several top execs, including a new chief financial officer, chief technology officer, chief customer officer, chief digital officer, and chief transformation officer. Napoli has also cut in half the number of people who directly report to him and in June directed the company to lay off 18% of its workforce, or around 1,500 employees, just four months after the EV maker made a cut of 12%. Lucid also eliminated the second shift of EV production at its factory in Casa Grande, Arizona. The layoffs and elimination of that second shift generated $158 million in projected annualized savings, Napoli said during the company’s earnings call. Despite these moves, Lucid’s second-quarter earnings show a company that continues to lose money. The EV maker reported revenue of $405 million, up from $259.4 million in the same quarter last year. It reported a net loss of $1.26 billion, or $3.30 a share, compared with a loss of $855.3 million, or $2.80 a share, a year earlier. Lucid said it ended the second quarter with $3 billion in total liquidity. While a reduction in spending is central to this reset, Napoli listed several must-win projects, including its upcoming mid-sized EV, finishing its AMP-2 factory in Saudi Arabia, and its robotaxi program with Uber and Nuro, that will eventually make it profitable. The midsize EV, known as Cosmos, will be the first model from Lucid’s mid-sized platform, which “remains an essential element of Lucid’s strategic plan,” Napoli said. Napoli is also bullish on its robotaxi program with Uber and Nuro and sees it as an opportunity to boost earnings outside of selling directly to consumers. In a sign of this program’s value to Lucid, the company has created a new business unit called Lucid Technologies that will be led by chief digital officer Kai Stepper. The new unit will focus on AI, advanced driver assistance system, and digital technology. “We project the margins vastly exceeding those of the traditional retail model,” Napoli said, referring to the robotaxi program that integrates Nuro’s self-driving technology into Lucid’s Gravity SUVs. Uber will operate the premium robotaxi service, which will allow users to hail the self-driving vehicles on its app. Nuro and Uber are testing fleet of 100 vehicles in Houston and the San Francisco Bay Area and Houston. The company said that last month it began delivering production validation vehicles assembled at a facility in Coolidge, Arizona. Regular vehicle production for the robotaxi will begin in the fourth
On Tuesday, AI infrastructure company Runware announced the launch of its own modular data center called Sonic Inference Pod. Designed as a single transportable unit, the Pod represents a more flexible kind of compute that can sit alongside hyperscalers’ massive data center projects. Runware says the Pod can offer inference at a higher quality but lower cost than other serverless inference platforms and GPU clouds. The modular design means it’s easy add capacity quickly by creating new pods rather than having to expand a fixed data center. In some ways, this is the future, Flaviu Radulescu, co-founder and CEO of Runware, told TechCrunch. “We believe distributed compute, positioned closer to end users for faster inference, is what will win in the long term,” he said, noting his company as an example. Aside from a lower price, Radulescu noted that the runware system can scale and add capacity fast, deploy anywhere there is power, and adapt quickly to new hardware releases. The Runware pods also do not use water, but rather a closed-loop cooling system that can be built in days, compared to the months or even years it takes to build traditional data centers. “Demand for inference is growing faster than facilities can be built,” Radulescu said. “What we want is to power the world’s intelligence, to be the backbone every AI model runs on with capacity that keeps up with demand instead of throttling it.” Runware currently has 10 pods in deployment across the U.S., Europe, and Asia-Pacific, Radulescu said. The company already provides inference to a few companies, including Higgsfield AI and Wix, and has 160 sites available to power its pods right now. Runware announced a $50 million Series A in December to provide the infrastructure needed for companies to generate images. They see the expansion into pods as part of the company’s core mission: providing inference to companies, rather than a single product. Image Credits:Runware AI labs like OpenAI and SpaceX are still racing to build data centers throughout the U.S. OpenAI, for example, is close to striking a $500 billion deal that would see it build a data center in Ohio, according to reports. But Radulescu doesn’t see those projects as a threat to the Sonic Inference Pods, describing the flexibility of the pods as a key differentiator. “Every pod runs as part of a single network, so requests go wherever there’s capacity, closer to the users, and if one pod goes offline, traffic moves to another,” he said, adding that a system failure means one pod is down rather than a whole fixed facility. “Customers who want dedicated hardware get whole pods to themselves.” He’s also not too worried about other companies building this for themselves, saying simply that hardware is slow and finding the talent pool to build and fix this technology is small. “A mistake in a circuit board design costs months between redesign, simulation, fabrication, testing and delivery,” he said. “Every one of those calls needs someone who understands exactly what each component does and what breaks if it’s gone.” Building AI data centers is a controversial topic, however, especially because of how many resources it uses. Already, communities where data centers are located have reported seeing a rise in utility costs. One day, Runware sees a world where it can run on renewable power and doesn’t draw on the resources communities need, but that day is not necessarily today. Radulescu said that AI power use is going to increase regardless, “driven by demand for inference, not by who supplies it.” What Runware is focused on right now is how that demand gets met, he said. “No transmission losses, no water in cooling, and we’re using power that already exists instead of asking for new grid capacity to be built. More inference built this way means less new grid, less water, for the same amount of compute.” When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our
Monday.com, the Tel Aviv-based work management software company known for its colorful, customizable project-tracking boards, this week became the latest tech company to cite AI as a factor in job cuts. On Wednesday, the company said in an SEC filing that it will lay off about 20% of its workforce, or just over 600 employees, as part of a “restructuring plan” tied to its “ongoing transformation of its product, marketing, and go-to-market strategy” in support of “a leaner, more focused operating model” as it continues investing in its “AI-driven growth strategy.” Co-founder Eran Zinman told employees in a LinkedIn memo that the move “was not made to reduce costs or replace people with AI,” positioning it instead as adapting the organization to a new AI-first vision the company laid out roughly a year ago when it rebranded around a platform-wide AI push. Monday.com, which has two offices in the U.S., expects $45 million to $55 million in net restructuring charges but still projects up to 20% year-over-year revenue growth for 2026. So far, according to new Financial Times analysis, U.S. tech companies have slashed nearly 140,000 jobs since the start of this year, with Amazon, Oracle, Meta, and Microsoft alone accounting for almost 50,000 of those cuts as they funnel hundreds of billions of dollars into AI data center buildouts. Interestingly, the FT also found that companies citing AI as a factor in job cuts have underperformed the Nasdaq by almost 10% in the 30 trading days following their announcements, suggesting the market doesn’t entirely buy the stories that the companies are telling. Still, the picture isn’t uniformly bleak. The FT notes that AI-focused companies like Anthropic and OpenAI are hiring rapidly, absorbing some of the talent shed elsewhere in the industry. And within some of the very companies making cuts, headcount is shifting rather than simply shrinking: Meta, for instance, earlier this year moved roughly 7,000 employees into new AI-focused roles even as it laid off 8,000 others, and IBM says it’s tripling entry-level hiring for AI and hybrid-cloud roles alongside recent cuts. Below is a running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor. Microsoft — July 9, 2026. Microsoft cut about 4,800 roles, or 2.1% of its global workforce, most of them in its Xbox gaming unit, resetting the business only three years after acquiring Activision Blizzard for $75 billion, per the FT. Separately, it offered buyouts structured as voluntary separations, without disclosing how many employees these would impact. The company said the role eliminations were “not being replaced by AI” but acknowledged “AI is changing how work gets done.” CFO Amy Hood said total headcount declined year-over-year in fiscal Q3, and was expected to keep declining as the company focuses on “building high-performing teams that operate with pace and agility” amid rising AI investment. Oracle — June 22, 2026. Oracle disclosed in late June that it had reduced its workforce by 21,000 employees over the past 12 months, a decline of 13%, which means more cuts than was previously known, including because of AI. “The adoption and deployment of AI technologies across our operations have resulted, and may continue to result, in reductions to our workforce,” the company said in an annual financial regulatory filing. GitLab — June 3, 2026. GitLab laid off roughly 350 workers, about 14% of its staff, to fund AI infrastructure investment and handle surging traffic from AI workflows. CEO Bill Staples said agentic workloads are “pushing competitors to the brink” and that the company had begun a “generational rebuild” of its core infrastructure to support what he called 100x growth requirements. GitLab is exiting 22 countries, flattening management layers, and partnering with an unspecified AI lab to rebuild its platform for agent-scale workloads. The company re
OpenAI launched its first piece of hardware last week — a fancy little keypad built to pair with ChatGPT. Micro, which was developed in collaboration with specialty keyboard designer Work Louder, is essentially an artisanal workplace novelty that many tech enthusiasts will love and that may leave everyone else a little puzzled. OpenAI’s entrance into the hardware market hasn’t arrived without drama. Several weeks ago, Apple sued the AI lab and accused it of trade theft — kicking off what’s certain to be a long-simmering legal battle. Meanwhile, news of another smart home product in development at OpenAI has also raised eyebrows, as the supposed device — which is being built to pair with ChatGPT — was reportedly developed by former Apple engineers. Until the legal battle works itself out and OpenAI’s broader hardware ambitions materialize, the most the startup has to offer is Micro — a funky little keypad clearly engineered to delight the tech industry’s code monkeys. OpenAI sent TechCrunch a Micro test unit. The first big thing you notice when initially handling the keypad is that it’s a sturdy little device — enough so that if the AI accessory thing doesn’t end up working out, it could easily double as a paperweight. The other thing you might notice (and I am not the only one to point this out), is that the packaging — an immaculate white box with a sleek, clean aesthetic — is pretty Apple-coded. Make of that what you will. The keypad’s layout involves six frosted “agent” keys at the top of the pad, which can be customized to carry out specific tasks within ChatGPT or its agentic coding tool Codex. Below them are six command keys, which can be used to control those programs. You can pair your Micro with your computer either through a Bluetooth connection or a USB cable. Image Credits:Lucas Ropek/TechCrunch Perhaps the most convenient thing Micro offers is a button for voice dictation — meaning you simply tell the app what you want done and it will get busy working on your behalf. Just hold down the dictation button and start talking. When you’re done, tap the “send” button next to it to submit your request. You can customize your Micro keypad within ChatGPT itself, where a Micro tab allows you to adjust everything from the brightness of the light from the keys to the specific commands and projects you want tied to those keys. Hard-core coders — the device’s actual target audience — haven’t exactly embraced it. Reviews by Redditors have largely negative, with one Reddit user calling it “a prank and not a real product,” and others saying serious coders won’t touch it. A review by the smaller independent outlet Aftermath was even harsher, calling the $230 price tag hard to justify next to cheaper DIY and off-the-shelf alternatives. (The title of that review: “OpenAI’s expensive macropad feels engineered to piss me off specifically.”) It’s definitely the case that new users may need some time to figure out how Micro works and what to do with it. Once I figured out how to program the keypad to my liking, I found it was actually pretty fun. You can assign various ChatGPT sessions to specific keys, which then allows you to easily toggle back and forth between all of your various projects. When you combine that with the dictation button, it makes the whole experience considerably more efficient and enjoyable. But there’s still a learning curve. Micro’s buttons are color-coded. White means an agent is idle, blue means its thinking, green means a task is complete, and red means there’s been an error. You’ll need to memorize that, along with memorizing which specific projects are coded to each key. The big question is whether the Micro keypad is functionally easier to use than just continuing to work on your laptop. In short: Why would I spend a week learning how to program and operate this thing when I already know how to use my computer’s mouse and keyboard? Ultimately, your experience with the Micro will depend heavily o
OpenAI said today it is making ChatGPT Health, a feature that helps users with health-related queries, available to all U.S.-based users over 18 across all plans. The announcement comes a day after a Florida-based pastor sued the company for giving a near-fatal suggestion not to consult a doctor. The company started testing the feature through a dedicated hub earlier in January, allowing users to integrate data from other services and their personal information from services such as Apple Health, Function, and MyFitnessPal. At that time, OpenAI said users were asking 230 million health-related queries each week. That number has now gone up to 300 million. Users can also integrate their medical records from hospital systems like Epic and Oracle Health, and health platforms like One Medical and Function Health. OpenAI said earlier that users needed to use the health hub for health-related queries. Now they can choose to draw insights from connected information in the health section in all queries. The company said during the testing it observed that 70% of health-related queries took place outside the dedicated hub. Through this new feature, users can use their health information to get information on food or allergies in the general chat. The company noted that its models have made progress in answering health-related queries. The company noted that the smallest model from its latest release, GPT 5.6-Luna, outperforms GPT 5.5 on HealthBench evaluation, an open-source benchmark developed by the company to evaluate large language models (LLMs) on health queries. OpenAI said that it doesn’t use any user data to train its model, and it works with physicians to improve its models on health queries. Despite these performance gains, the company maintains in its terms that its services are “not intended for use in the diagnosis or treatment of any health condition.” The company cited these clauses in responses to the above lawsuit, and also told the New York Times that it is working on making health- or medicine-related answers safer. With the latest roll out, OpenAI said it wants people to verify information and take medical decisions based on professional advise. Several studies have highlighted that AI bots are not reliable for medical advice. However, this has not deterred companies like Anthropic and Google from launching health-related AI features. Health in ChatGPT is rolling out to logged-in U.S. users with free, Go, Plus, and Pro plans on the web and iOS this week. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence. Ivan covers global consumer tech developments at TechCrunch. He is based out of India and has previously worked at publications including Huffington Post and The Next Web. You can contact or verify outreach from Ivan by emailing im@ivanmehta.com or via encrypted message at ivan.42 on Signal. View Bio
Discussion (0)