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Cerence reports Q2 EPS 46c, consensus 30c

Cerence reports Q2 EPS 46c, consensus 30c

Reports Q2 revenue $78.01M, consensus $75.34M. 'I'm incredibly proud of what our team has accomplished. We surpassed the high end of our revenue and adjusted EBITDA guidance and posted our fourth consecutive quarter of positive free cash flow, demonstrating the high value we provide to the world's leading automakers as they work through the ongoing macro uncertainties and complexities facing the industry today,' said Brian Krzanich, CEO, Cerence (CRNC) AI. 'As we look to the future and based on currently available information, we believe we are well-positioned to continue supporting our customers as they work to bring an enhanced experience to their drivers. With Cerence xUI, we are partnering with OEMs as they contemplate and build their future infotainment platforms, as well as delivering enhanced user experiences via over-the-air updates as automakers upgrade their current systems to deliver next-gen features and capabilities to their drivers today.'
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OpenAI taps Google in unprecedented cloud deal despite AI rivalry, sources say: Reuters
OpenAI taps Google in unprecedented cloud deal despite AI rivalry, sources say: Reuters

CNBC

time2 minutes ago

  • CNBC

OpenAI taps Google in unprecedented cloud deal despite AI rivalry, sources say: Reuters

OpenAI plans to add Alphabet'sGoogle cloud service to meet its growing needs for computing capacity, three sources told Reuters, marking a surprising collaboration between two prominent competitors in the artificial intelligence sector. The deal, which has been under discussion for a few months, was finalized in May, one of the sources added. It underscores how massive computing demands to train and deploy AI models are reshaping the competitive dynamics in AI, and marks OpenAI's latest move to diversify its compute sources beyond its major supporter Microsoft, including its high-profile Stargate data center project. It is a win for Google's cloud unit, which will supply additional computing capacity to OpenAI's existing infrastructure for training and running its AI models, sources said, who requested anonymity to discuss private matters. The move also comes as OpenAI's ChatGPT poses the biggest threat to Google's dominant search business in years, with Google executives recently saying that the AI race may not be winner-take-all. OpenAI, Google and Microsoft declined to comment. Alphabet's stock was up 2.1% on Tuesday afternoon following the news, while Microsoft shares were down 0.6%. Scotiabank analysts called the development "somewhat surprising" in a note on Tuesday, highlighting the growth opportunities for Google's Cloud unit, while expressing caution regarding competition from ChatGPT. "The deal ... underscores the fact that the two are willing to overlook heavy competition between them to meet the massive computing demands. Ultimately, we view this as a big win for Google's cloud unit, but ... there are continued worries that ChatGPT is becoming an incrementally larger threat to Google's search dominance," the analysts wrote. Since ChatGPT burst onto the scene in late 2022, OpenAI has dealt with increasing demand for computing capacity - known in the industry as compute - for training large language models, as well as for running inference, which involves processing information so people can use these models. OpenAI said on Monday that its annualized revenue run rate surged to $10 billion as of June, positioning the company to hit its full-year target amid booming adoption of AI. Earlier this year, OpenAI partnered with SoftBank and Oracle on the $500 billion Stargate infrastructure program, and signed deals worth billions with CoreWeave for more compute. It is on track this year to finalize the design of its first in-house chip that could reduce its dependency on external hardware providers, Reuters reported in February. The partnership with Google is the latest of several maneuvers made by OpenAI to reduce its dependency on Microsoft, whose Azure cloud service had served as the ChatGPT maker's exclusive data center infrastructure provider until January. Google and OpenAI discussed an arrangement for months but were previously blocked from signing a deal due to OpenAI's lock-in with Microsoft, a source told Reuters. Microsoft and OpenAI are also in negotiations to revise the terms of their multibillion-dollar investment, including the future equity stake Microsoft will hold in OpenAI. For Google, the deal comes as the tech giant is expanding external availability of its in-house chip known as tensor processing units, or TPUs, which were historically reserved for internal use. That helped Google win customers including Big Tech player Apple as well as startups like Anthropic and Safe Superintelligence, two OpenAI competitors launched by former OpenAI leaders. Google's addition of OpenAI to its customer list shows how the tech giant has capitalized on its in-house AI technology from hardware to software to accelerate the growth of its cloud business. Google Cloud, whose $43 billion in sales comprised 12% of Alphabet's 2024 revenue, has positioned itself as a neutral arbiter of computing resources in an effort to outflank Amazon and Microsoft as the cloud provider of choice for a rising legion of AI startups whose heavy infrastructure demands generate costly bills. Alphabet faces market pressure to demonstrate financial returns on its AI-related capital expenditures, which are expected to hit $75 billion this year, while maintaining its bottom line against the threat of competing AI offerings, as well as antitrust enforcement. Google's DeepMind AI unit also competes directly with OpenAI and Anthropic in a race to develop the best models and integrate those advances into consumer applications. Selling computing power reduces Google's own supply of chips while bolstering capacity-constrained rivals. The OpenAI deal will further complicate how Alphabet CEO Sundar Pichai allocates the capacity between the competing interests of Google's enterprise and consumer business segments. Google already lacked sufficient capacity to meet its cloud customers' demands as of the last quarter, Chief Financial Officer Anat Ashkenazi told analysts in April. Although ChatGPT holds a large lead over Google's competing chatbot in terms of monthly users and analysts have predicted it could reduce Google's dominant search market share, Pichai has brushed aside concerns that OpenAI will usurp Google's business dominance.

AI Time Platform Laurel Raises $100 Million to Transform the Professional Services Industry
AI Time Platform Laurel Raises $100 Million to Transform the Professional Services Industry

Business Wire

time8 minutes ago

  • Business Wire

AI Time Platform Laurel Raises $100 Million to Transform the Professional Services Industry

SAN FRANCISCO--(BUSINESS WIRE)--Laurel, the world's first AI Time platform, today announced it has raised $100 million in Series C funding led by IVP, with participation from GV (Google Ventures). Laurel will leverage this investment to scale its AI time platform and accelerate to solve what it calls the 'time intelligence challenge"—the inability for knowledge industries to accurately map time to business outcomes. In the age of AI, quantifying and understanding human capital goes from a 'nice to have' to a 'cannot exist without' for enterprises. In addition to IVP and GV, new investors in the round, which consists of primary and secondary funding, also include: 01.a (created by former CEO and COO of Twitter & CRO of Facebook), DST Global, Kevin Weil (CPO @ OpenAI), Alexis Ohanian, Vladimir Fedorov (CTO @ GitHub), Arash Ferdowsi (co-founder of Dropbox), and Hans Tung. These investors join returning investors ACME, Anthos, Gokul Rajaram, AIX Ventures, and Marc Benioff's TIME Ventures. The funding comes as Laurel experiences rapid adoption among enterprise professional services firms like Ernst & Young, Grant Thornton, Freshfields, and Crowell & Moring. Over the last 12 months, Laurel grew ARR +300% at double-digit scale, increased usage by +500%, and works with +100 of the top legal, accounting, and consulting firms across US, UK, EU, Australia, and Canada. Laurel's AI Time platform, now leveraged by hundreds of the world's top enterprise professional service firms, uses AI to automatically categorize, describe, and analyze how professionals spend their time on admin work. The platform's ability to connect time data with business outcomes has proven transformative for firms looking to maximize profits, allocate their resources effectively, and understand exactly what workflows to apply AI to and what agents to automate. Customers using the company's AI-native time platform report profit increases between 4-11%—driven by an additional 28 billable minutes per day per professional, and increased realization of 1-4%. Laurel's ROI methodology has been independently audited and validated by a Big-4 Firm. The platform currently processes over $5B in gross market value for its customers, and +$360M of that amount is net-new value attributable to Laurel. In addition, Laurel saves its professionals up to 80% in time recording, freeing them to work on high-leverage work. 'Laurel uniquely delivers value across lawyers, clients, finance, and marketing by streamlining time capture, enriching narratives, and accelerating accurate billing,' says Reed Cunningham, Chief Innovation Officer at global law firm Reed Smith. 'As firms assess the impact of AI and fixed fees, gaining granular intelligence with less effort is essential to redefining value within a firm and for its clients.' 'I've seen first-hand how Laurel can transform our approach to time intelligence. What used to be a manual process of time-keeping and entry is now significantly technology enabled,' says Matt Newnes, Partner and Tax Transformation leader at Ernst & Young. 'Laurel doesn't just help our people to capture time that they spend on work more comprehensively; it helps us to understand much more about how our teams work allowing us to identify best practices to help ensure we always drive the best outcomes for our clients. It has proven to be one of our most impactful AI investments, delivering measurable results while laying the foundation for broader transformation initiatives.' Automating time is Laurel's first step. Laurel's AI platform turns its proprietary data around work and time to address the #1 business problem impacting knowledge industries: operating without visibility into their supply chain. 'Nobody has ever mapped the input of time to the output of outcomes. Industries like legal and accounting are best at understanding their input (time), but still struggle to price value. On the flip side, industries like consulting and financial services understand value, but operate blind to the true cost of creation. While all other industries have been obsessed about optimizing their supply chain, the supply chain of knowledge work—which represents over 50% of Global GDP—has never been surfaced. This funding helps us solve this fundamental challenge while giving firms the data foundation they need to deploy AI strategically. We're not just automating time—we're creating the time intelligence layer that will transform how all knowledge industries operate," says Ryan Alshak, founder and CEO of Laurel. "Laurel has identified one of the largest efficiency gaps in the modern economy, one I understand deeply as a former CFO of a public company. Professional services represent trillions in global economic activity, yet these firms operate without basic visibility into their core resource – time. By solving the time intelligence challenge, Laurel creates a platform for broader AI transformation. As these industries invest heavily in AI over the next five years, Laurel's data foundation becomes essential infrastructure that truly tracks the ROI of AI. The market opportunity is massive, and Laurel's unique position makes them the clear leader in this space," says Ajay Vashee, General Partner at IVP. 'Laurel is creating the enterprise intelligence layer for knowledge work that leverages timekeeping as a product wedge,' said Frederique Dame, General Partner at GV. 'By capturing and organizing the full lifecycle of how professionals spend their time, Laurel unlocks a new class of data that makes work itself measurable, optimizable, and automatable. The goal isn't just better time tracking, it's building the data foundation for AI-powered workflows, predictive resourcing, and strategic insights.' Transforming How Knowledge Industries Understand and Optimize Work While manufacturing companies know exactly how much it costs to produce a car down to the penny, and retail businesses track inventory with precision, professional services firms have historically operated without understanding their most critical resource: human capital. Both the outcomes of the work itself and the time it takes to produce it. As a result, organizations are operating blind on what the biggest impact for AI is across their companies, and how to point people to highest value tasks (like Business Development, Relationship Management, and first principles strategic thinking). As knowledge industries plan to spend over $1 trillion on AI in the next five years, Laurel's time intelligence platform ensures these investments target the highest-impact opportunities. Key customer results include: Average recovery of 28+ billable minutes per professional per day 4-11% increase in overall firm profitability 80%+ reduction in time spent on manual time entry Real-time visibility into project profitability and resource utilization 'While Laurel is unique in that it is AI that generates profits, the reason everyone at Laurel cares so much about solving this problem is because people waste so much time at work, and the only way to solve this at scale is to deeply understand where that time is going,' says Alshak. 'And we're starting with professional services because that will give us the human-in-the-loop required to create the world's first-ever agentic timesheet. The average knowledge worker works 9 hours a day, but only adds leverage for 3. That is 3 hours a day we're doing work that should be done by agents, and 3 hours a day we're doing work that nobody should do. That is our opportunity set – 6.4 billion years currently being spent by knowledge workers on tasks humans no longer need to do. That is our opportunity.' About Laurel Laurel is the world's first AI Time platform for professional services firms. The company's AI transforms how organizations track, analyze, describe, and optimize their most valuable resource: time. By automating work time and connecting time data to business outcomes, Laurel enables firms to increase profitability, improve client delivery, and make data-driven strategic decisions. Founded in 2018, Laurel serves many of the world's largest accounting, consulting and law firms. For more information, visit About IVP IVP supercharges growth in breakout companies, converting momentum into market dominance. One of the original venture firms on Sand Hill Road, IVP partners with companies that define their eras—from Slack, Crowdstrike and Coinbase to Perplexity, Abridge, Glean and Chainguard—before the world truly appreciated them. Each year, IVP invests in just a dozen breakout founders ready to scale from millions to hundreds of millions in revenue and expand from one market to many. We've guided market leaders through cycles and storms, unlocking pivotal growth by activating the right expertise at the moments founders need it. With 130+ IPOs out of 400 investments, IVP helps ambitious founders defy limits, command industries and cement their place at the top.

A Computer Wrote My Mother's Obituary
A Computer Wrote My Mother's Obituary

Atlantic

time21 minutes ago

  • Atlantic

A Computer Wrote My Mother's Obituary

The funeral director said 'AI' as if it were a normal element of memorial services, like caskets or flowers. Of all places, I had not expected artificial intelligence to follow me into the small, windowless room of the mortuary. But here it was, ready to assist me in the task of making sense of death. It was already Wednesday, and I'd just learned that I had to write an obituary for my mother by Thursday afternoon if I wanted it to run in Sunday's paper. AI could help me do this. The software would compose the notice for me. As a professional writer, my first thought was that this would be unnecessary, at best. At worst, it would be an outrage. The philosopher Martin Heidegger held that someone's death is a thing that is truly their own. Now I should ask a computer to announce my mother's, by way of a statistical model? 'Did you say AI?' I asked the funeral director, thinking I must have been dissociating. But yes, she did. As we talked some more, my skepticism faded. The obituary is a specialized form. When a person of note dies, many newspapers will run a piece that was commissioned and produced years in advance: a profile of the deceased. But when a normal person dies—and this applies to most of us—the obituary is something else: not a standard piece of journalistic writing, but a formal notice, composed in brief, that also serves to celebrate the person's life. I had no experience in producing anything like the latter. The option to use AI was welcome news. After all, there were lots of other things to do. The obituary was one of dozens of details I would have to address on short notice. A family in grief must choose a disposition method for their loved one, and perhaps arrange a viewing. They must plan for services, choose floral arrangements or other accessories, select proper clothing for the deceased, and process a large amount of paperwork. Amid these and other tasks, I found that I was grateful for the possibility of any help at all, even from a computer that cannot know a mother's love or mourn her passing. The funeral director told me I would be given access to this AI tool in the funeral-planning online account that she had already created for me. I still had a few misgivings. Would I be sullying Mom's memory by doing this? I glanced over at an advertisement for another high-tech service—one that could make lab-grown diamonds from my mother's ashes or her hair. Having an AI write her obituary seemed pretty tame in comparison. 'Show me how to do it,' I said. Actually getting a computer to do the work proved unexpectedly difficult. Over the next 24 hours, the funeral director and I exchanged the kind of emails you might swap with office tech support while trying to connect to the shared printer. I was able to log in to the funeral portal (the funeral portal!) and click into the obituary section, but no AI option appeared. The funeral director sent over a screenshot of her display. 'It may look slightly different on your end,' she wrote. I sent a screenshot back: 'That interface is not visible to me.' Web-browser compatibility was discussed, then dismissed. The back-and-forth made me realize that Mom's memorial would be no more sullied by AI than it was by the very fact of using this software—a kind of Workday app for death and burial. In the end, the software failed us. My funeral director couldn't figure out how to give me access to the AI obituary writer, so I had to write one myself, using my brain and fingertips. I did what AI is best at: copying a formula. I opened up my dad's obituary, which Mom had written a couple of years earlier, and mirrored its format and structure. Dates and locations of birth and death, surviving family, professional life, interests. I was the computer now, entering data into a pre-provided template. When I finally did get the chance to try the AI obituary writer a few weeks later—after reaching out to Passare, the company behind it—I found its output more creative than mine, and somehow more personal. Like everything else, the funeral-services industry is now operated by cloud-based software-as-a-service companies. Passare is among them, and offers back-office software for funeral-home management along with family-facing funeral-planning tools. Josh McQueen, the company's vice president of marketing and product, explained why my earlier attempt to use the obituary-writing tool had failed: The funeral home must have had that feature set for staff-only access, which some businesses prefer. Then he gave me access to a mock funeral for the fictional departed John Smith so I could finally give it a go. I couldn't change John Smith's name, but I pretended I was writing the obituary for my mother instead. Using simple web forms, I put in her education and employment information, some life events that corresponded to her 'passions' and 'achievements,' and a few facts about relevant family members who had survived her or preceded her in death. These had to be entered one by one, choosing the type of relation from a drop-down and then checking a box to indicate whether the person in question was deceased. I felt like I was cataloging livestock. From there, Passare's software, which is built on top of ChatGPT technology, generated an obituary. And you know what—it was pretty good. Most of all, it was done, and with minimal effort from me. Here's an excerpt, with John Smith's name and pronouns swapped out for my mother's, and a couple of other very small alterations to smooth out the language: Sheila earned her bachelor's degree and dedicated her career to managing her late husband David's psychology private practice for decades. She was not only devoted to his work but also a dedicated caregiver for Dave in his later years. Throughout her life, Sheila nurtured his passions, which included playing music—especially the piano—and a deep appreciation for Native American art. She found joy in teaching skiing to children and sharing the vibrant personalities of her many pet birds. The AI obituary can also be tuned by length and tone—formal, casual, poetic, celebratory. (The poetic version added flourishes such as 'she found joy in the gentle keys of her piano, filling her home with music that echoed her spirit.') Because an obituary is already a schematic form of writing, the AI's results were not just satisfactory but excellent, even. And, of course, once the draft was done, I could adjust it as I wished. 'When we first started testing this, ChatGPT would just make up stories,' McQueen told me. It might assert that someone named Billy was often called Skippy, for example, and then concoct an anecdote to explain the fake nickname. This tendency of large language models, sometimes called hallucination, is caused by the technology's complex statistical underpinnings. But Passare found this problem relatively easy to tame by adjusting the prompts it fed to ChatGPT behind the scenes. He said he hasn't heard complaints about the service from any families who have used it. Obituaries do seem well suited for an AI's help. They're short and easy to review for accuracy. They're supposed to convey real human emotion and character, but in a format that is buttoned-up and professional, for a public audience rather than a private one. Like cover letters or wedding toasts, they represent an important and uncommon form of writing that in many cases must be done by someone who isn't used to writing, yet who will care enough to polish up the finished product. An AI tool can make that effort easier and better. And for me, at least, the tool's inhumanity was also, in its way, a boon. My experience with the elder-care and death industries—assisted living, hospice, funeral homes—had already done a fair amount to alienate me from the token empathy of human beings. As Mom declined and I navigated her care and then her death, industry professionals were always offering me emotional support. They shared kind words in quiet rooms that sometimes had flowers on a table and refreshments. They truly wanted to help, but they were strangers, and I didn't need their intimacy. I was only seeking guidance on logistics: How does all this work? What am I supposed to do? What choices must I make? A person should not pretend to be a friend, and a computer should not pretend to be a person. In the narrow context of my mom's obituary, the AI provided me with middle ground. It neither feigned connection nor replaced my human agency. It only helped—and it did so at a time when a little help was all I really wanted.

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