🚀 Zaprep: Sosialmu Supercharged. Mulai gratis — otomasi 1.000 DM/bulan & ubah engagement jadi lead. dengan 1.000 DM otomatis/bulan.
Kirim Alatmu
PoweredByAI.app adalah Direktori Alat AI yang membantu individu, bisnis, dan kreator menemukan alat AI terbaik untuk menulis, coding, desain, produktivitas, dan lainnya.
© 2026 , Produk dari011BQ. Hak cipta dilindungi.
Book your exhibit table by Friday, September 18 at 11:59 p.m. PT.Tables are limited and first-come, first-served. From October 13-15 at San Francisco’s Moscone West,10,000+ founders, investors, operators, and tech leaderswill walk intoTechCrunch Disrupt 2026looking for companies to invest in, products to use, partners to work with, and technologies worth paying attention to. Your startup can be one of the companies they discover. The DisruptExpo Hallis the highest-traffic part of the event, giving your team three days to put your company directly in front of the people you want to reach. Book an exhibit table and use it to: The package also includes access to the TechCrunch Disrupt press list, Silver Tier sponsor branding, and additional event recognition. And you don’t need to fit a specific startup profile to exhibit. Startups at any stage or in any industry can put their company on the Expo Hall floor. Don’t wait until the deadline to decide.Tables can sell out first. 4 days left.Book your exhibit table nowfor $12,500 before Friday’s 11:59 p.m. PT deadline. TechCrunch Disrupt 2026brings 250+ top-tier tech leaders across 200+ sessions on six industry stages, plus interactive sessions and AI-powered matchmaking designed to help you make more relevant connections. You’ll also discover 300+ startups and the Startup Battlefield 200 while connecting with the founders, investors, and operators shaping what’s next.Regular ticket pricing ends September 25.
View
AI has dramatically lowered the barrier to building impressive prototypes. Getting those prototypes into production is a different story. Every founder hopes their breakthrough becomes a product customers can rely on. Yet the path from prototype to production rarely follows a straight line. Manufacturing challenges emerge. Infrastructure has to support growth. Autonomous systems have to perform outside controlled environments. The problems change quickly once technology leaves the lab. That’s the focus of “From Prototype to Production: Can It Scale in Reality,” taking place on theReal World AI StageatTechCrunch Disrupt 2026. Leaders in space communications, autonomous systems, and AI infrastructure will share how they’ve navigated that transition, from promising innovation to production-ready deployment. Although every industry follows its own path, all three speakers have faced the same reality: A successful prototype is only the beginning. Disrupt returns to Moscone Westin San Francisco, October 13–15, bringing together 10,000+ founders, investors, and operators for 250+ sessions exploring the technologies and market forces shaping what’s next.Secure your Disrupt passto hear how today’s innovators are moving breakthrough technologies into production. A working prototype answers one question: “Can it be done?” Production raises dozens more. Building optical communications hardware has little in common with deploying autonomous vehicles or autonomous construction equipment. Yet each requires the technology to perform consistently outside controlled environments, where reliability, manufacturing, infrastructure, and day-to-day operations become integral to the product itself. ThisReal World AI Stage sessiondoesn’t promise a single blueprint. Instead, it brings together founders who have tackled production from very different angles, offering a rare opportunity to compare what scaling looks like across industries. Explore the Real World AI Stageand register for Disrupt with up to $200 savings. No two production stories look the same. That’s what makes this discussion compelling. Each foundertaking the Real World AI stagehas navigated a different path from prototype to production, offering lessons startups can apply to their own journey. Moving beyond the prototype often means building manufacturing capability alongside the technology itself. As co-founder and CEO ofMBRYONICS,John Mackeyhas transformed a specialized photonics spinout into a leader in space-based optical communications, expanding high-volume manufacturing while helping build the infrastructure behind next-generation space networks. His insights will help startups understand what changes when your company shifts from building prototypes to building products. Before co-foundingBedrock Robotics,Boris Sofmanhelped lead autonomous trucking and core technologies at Waymo, where fully driverless vehicles logged more than 100 million driverless miles. His experience reflects what happens when autonomous systems leave controlled testing and begin operating in environments where consistency and reliability matter every day. He’ll shed light on how to scale production while ensuring safety and reliability. Before co-foundingFoxglove,Adrian Macneilled infrastructure engineering at Cruise, developing the data platform that supported autonomous vehicles at scale. His work demonstrates that production depends on the engineering systems surrounding it. His talk will underscore the systems and infrastructure that allow complex technologies to move beyond experimentation and into everyday use. Together, they bring three different perspectives to the same milestone every ambitious technology company eventually reaches: moving from a successful prototype to something customers can trust in the real world. Hear how these founders approached production and what they learned along the way.Choose your Disrupt ticket type and save up to $200 by September 25. Sooner or later, every promising technology has to prove itself outside the lab. That’s where this Disrupt conversation begins. Rather than focusing on what’s possible in theory, these founders will discuss what happens when manufacturing, deployment, infrastructure, and day-to-day operations become part of the product. Regardless of the innovation you’re building, this session offers the opportunity to hear from founders who’ve already navigated the move from prototype to production — and the lessons they learned along the way. Secure your pass to Disruptand hear how leaders are making the leap from prototype to production. Save up to $200 before prices increase on September 25.
Companies have been increasingly using AI’s image generation chops to teach people photography skills. Google last year released a feature calledCamera Coach on Pixel phonesto guide users about framing and composition, and in July, Adobe released a new feature in its experimental camera app to use AI tocritique photos and suggest changes for capture. On the same slant, two former TikTok employees, Melody Chu and Jing Liu, are launching a new iOS app calledSuperposethat uses an AI guide to teach people how to pose for pictures. Superpose essentially is a camera app. Users can take a selfie or photo of a friend, and the app will generate four potential poses using AI. Some of the poses are extravagant, and, at times, the generation seems uncanny. Users can save generated poses, or use the match-pose feature to try to place themselves in the frame based on its suggestions. Prior to founding Superpose, Chu worked in various product roles in companies like Meta, Nextdoor, Roblox, TikTok, and Slack. Meanwhile, Liu was a founding engineer at a 3D face-scanning startup, and later worked on image and video models at TikTok. Chu said that the idea for the app stemmed from a personal problem: her husband wasn’t able to take good photos of her. “My husband just takes awful photos of me. It was a true pain point in our marriage where I don’t understand how he gets me to look just so terrible all the time. And I thought to myself, there has to be a way to solve this problem with advancements in computer vision and generative AI. And I decided to set out on my own,” Chu told TechCrunch. Superpose was launched in July, and has been downloaded over 22,000 times so far. The company says its users have generated more than 190,000 poses. The app gives users five generations for free every day, but they can buy a pack of five additional generations for $2.99, or 20 generations for $9.99. Loading the player… While Chu acknowledged that other companies are also entering the AI-guided photography space, she said Superpose wants to focus on becoming the best camera to take portrait photos by following directions from AI. The startup doesn’t want to get into creating AI backgrounds and images, and wants to focus on real-life photographs, she added. “We want to lean into the core of memory capture versus, say, putting you in a fantastical place that you’ve never been. I think there are so many apps that do that well already, but we really wanna focus on actually capturing the lived moment and experience,” Chu said. She also acknowledged that some of the pose suggestions might seem uncanny, and the company is working on improving that. The startup says it is working on improving its generation styles, personalization, and ways to better coach users directly from the viewfinder. Superpose has raised $2.2 million in funding from Khosla Ventures, Chinese smartphone and selfie app maker Meitu, and OVTR VC.
Profound, which builds marketing software to help brands appear in AI search results, on Tuesday said it has raised a $180 million Series D at a $1.8 billion valuation, less than seven months after it raised a $96 million Series C. Sequoia and Kleiner Perkins led the round, and existing investors — including Lightspeed Venture Partners, Khosla Ventures, and South Park Commons — also participated. Launched two years ago, Profound started as an analytics platform, and has since expanded to help companies research and create marketing strategies. The startup helps businesses understand how AI helps consumers discover their brands. It’s part of a wave of startups in theGEO/AEO space(generative engine optimization and answer engine optimization, respectively), where companies try to find ways to surface their products in the AI systems customers are increasingly using for search. The company says its revenue has increased by 3x in the past six months, and it now has more than 1,000 enterprise customers, which include Comcast, The Estée Lauder Companies, and Walmart.
View
Chris Lehane, OpenAI’s global policy chief, told reporters on Tuesday that the company has been working with rivals Anthropic and Google DeepMind on AI safety for weeks, as first reported byBloomberg. Lehane is reportedly in Washington to work with U.S. lawmakers addressing catastrophic risks associated with AI. The revelation comes in the wake ofAnthropic CEO Dario Amodei’s essay, published Saturday, which called for the industry to work together to slow the pace of frontier AI and avoid catastrophic risks. AI leaders across the industry, includingOpenAI’s Sam Altman,Google’s Demis Hassabis, andSpaceXAI’s Elon Musk, supported Amodei’s letter and call to action, with Altman saying that OpenAI would join Anthropic in embedding third-party evaluators into the company to monitor for safety. On Tuesday, Lehane admitted that the three companies have been in talks for several weeks regarding AI safety. Some, including Altman, have noted that such talks could put the companies at risk of violating antitrust law if the coordination is found to suppress competition. Amodei’s essay proposed a narrow government waiver allowing such safety coordination, but Lehane reportedly said the firms don’t need one. The news confirms earlier reporting and hints that the companies were working together. In an interview withFortune late last week, Altman hinted that he had been in private discussions with other AI leaders. This week,The Information reportedthat the three companies have been working together to create a standards body for the AI industry — something Altman reportedly told staff would need to happen without the support of the U.S. government. Hassabis called on the U.S. in July to establish anew standards bodyto act as an AI watchdog, with the power to screen the world’s most advanced models and coordinate industrywide slowdowns if dangers progressed. President Trump, for his part, hasdismissed safety concernsas ahoaxand pushed back on the need for tighter regulations, saying any slowdown would give China a leg up in the race. His key AI advisor David Sacks — a longtime investor with apersonal stakein much of the industry —echoed this, saying fears of existential risk from AI were overblown. At the same Tuesday meeting,Lehane saidthat OpenAI supports a provision in the FRONTIER Act that would force top frontier labs to allow “independent verification organizations” into their companies to ensure models are developed safely. TechCrunch has reached out to Anthropic, Google, and OpenAI for comment.
New features in Java 27 target secure enterprise communications, faster data processing, and lower JVM memory overhead.
View
A new AI model calledKoais one of the biggest announcements from Salesforce this week at its giant Dreamforce tech conference. Koa is the company’s first reasoning model, built on Nvidia’sopen-weight Nemotronmodel. The two companies worked together to post-train Koa to excel at sales, marketing, and customer-support-related tasks. Koa is a shining example of how the enterprise world’s needs for AI are diverging from what the frontier labs are offering. Proprietary AI labs would rather have enterprises uploading files, code, prompts, and feedback directly into their models and agents,and spending millionsto do so. But with the model, Salesforce is offering its enterprise customers: Koa will be provided as an alternative to the other models Salesforce offers in its Agentforce platform, where its customers build agents to handle rote tasks like answering customer service questions or scheduling appointments. “We’ve built many small task-specific language models, which are part of Agentforce’s portfolio,” Jayesh Govindarajan, EVP of Salesforce AI, told TechCrunch. “But reasoning has always been something that we’ve relied on the frontier model providers for. Until now.” Before Koa, if an agent needed to reason through a long-running or multi-step task, those prompts would be routed to a frontier model like Claude or ChatGPT through Agentforce’s AI gateway (the system that decides which model handles which request). “One of the reasons we hadn’t done this before, train our own enterprise-grade frontier model — we always wanted to — but the challenge has always been the lack of a pre-trained base model to start with. Until Nemotron came along, there was no sovereign American pre-trained model that was available, one, and two, that was state of the art, and, three, that had clear data provenance. We have no idea what Qwen trains on,” Govindarajan said, referring to the popular Chinese open-weight model produced by Alibaba. Post-training a model like this means taking it from a general-purpose system to one well-versed in sales and customer support knowledge, and to do that, Salesforce and Nvidia did not use any actual data from Salesforce’s customers. Instead, they crafted synthetic data that mimicked customers’ patterns. “We actually simulated a customer service environment with a persona customer service professional, including irate customers that call into the customer service center, all the way to a sales professional who’s trying to close a deal,” Govindarajan described. Koa is meant to be better at the work tasks Salesforce customers want an agent to do — and cheaper, in terms of tokens burned — than sending those same tasks to Claude or ChatGPT. With Nemotron, “we have a unique architecture for inference to be token efficient,” Kari Ann Briski, Nvidia’s VP of Generative AI Software for Enterprise, told TechCrunch. “It’s kind of the trifecta of things that you need to have: sovereign AI, time to first token, efficient reasoning, for the tokenomics of it all.” However, Salesforce isn’t exactly abandoning Anthropic or OpenAI. It just announced a partnership with Anthropiccalled ClaudeForcethat allows companies to use Claude as their AI interface, while their data remains in Salesforce’s system of records, secured by its infrastructure.
The new office will support chipmakers and electronics manufacturers as India expands domestic fabrication, packaging and testing.
View
NVIDIA has added an orchestration layer and benchmark tools to help researchers develop practical quantum computing systems.
View
CoRover.ai said its 2B-parameter BharatGPT-Instruct model has surpassed the much larger Sarvam 30B on several reasoning, fairness, and multilingual benchmarks.
View
HCLTech and CrowdStrike are expanding their partnership to help enterprises secure AI applications, models, and agents.
View
Dassault Systèmes is pushing AI beyond design assistance, combining simulation, digital twins, and AI agents to help enterprises explore more designs.
View
View
View
View
View
