logo
Q.ANT and IMS CHIPS Launch Production of High-Performance AI Chips, Establish Blueprint for Strengthening Chip Sovereignty

Q.ANT and IMS CHIPS Launch Production of High-Performance AI Chips, Establish Blueprint for Strengthening Chip Sovereignty

Stuttgart, Germany--(Newsfile Corp. - February 25, 2025) - Q.ANT, a pioneer in photonic processing for AI, has launched a dedicated production line for its high-performance photonic AI chips at the Institute of Microelectronics Stuttgart (IMS CHIPS), marking a significant semiconductor manufacturing milestone. By integrating Q.ANT's patented photonic chip technology on the base of Thin-Film Lithium Niobate (TFLN) material and upcycling the existing CMOS production facility at IMS CHIPS, the partners have established a first-of-its-kind manufacturing line to accelerate the production of energy-efficient, high-performance processors for AI applications. Q.ANT has invested 14 million in machinery and equipment to complement the new line for photonic chips.
To view the full announcement, including downloadable images, bios, and more, click here.
Key Takeaways:
Addressing AI's most pressing challenges: computational complexity and soaring energy demands
Offering a breakthrough in computing speed and efficiency for AI/HPC workloads
Establishing a blueprint for scalable, sustainable chip manufacturing
[ This image cannot be displayed. Please visit the source: ]
Click image above to view full announcement.
About IMS CHIPS
IMS CHIPS, Institute for Microelectronics Stuttgart, conducts business-oriented research in the field of microelectronics in the areas of silicon photonics, integrated circuits and systems, nanostructuring and MEMS. It is a recognized non-profit foundation under civil law and is located on the Stuttgart-Vaihingen research campus. The institute is a member of the Innovationsallianz Baden-W"urttemberg (innBW), a cooperation of ten contract research organizations in Baden-W"urttemberg comprising a total of twelve institutes.
About Q.ANT
Q.ANT is a deep tech company advancing photonic computing and quantum sensing. Its native sensing technology enables ultra-precise detection of electric and magnetic fields, while its native computing division develops photonic processors that use light to process information, delivering unprecedented efficiency for AI and high-performance computing (HPC). Based on the Q.ANT Para.Digm framework, its technology overcomes the limitations of conventional electronics unlocking new possibilities in AI, medical technology, aerospace and manufacturing. Founded in 2018 as a spin-off from TRUMPF, Q.ANT is headquartered in Stuttgart, Germany.
Contacts:
1- 843-530-4442
Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

Gemini on Android may soon support the full range of Canvas creation options (APK teardown)
Gemini on Android may soon support the full range of Canvas creation options (APK teardown)

Android Authority

time2 minutes ago

  • Android Authority

Gemini on Android may soon support the full range of Canvas creation options (APK teardown)

Edgar Cervantes / Android Authority TL;DR Earlier this year, Google Gemini introduced Canvas for working with documents. Canvas on the web allows you to create things like apps, Audio Overviews, and infographics straight from your docs. Now it looks like Google's working to bring the same option to the Gemini mobile app. On-device AI models like Gemini Nano are very impressive for what they're able to do within some serious hardware constraints, but when it comes to AI solutions capable of some real heavy lifting, we still turn to cloud-hosted services the majority of the time. And while that's totally workable, it does leave us feeling just a wee bit frustrated when we don't have the same features available to us across platforms. Gemini's slowly been getting better in this regard, bringing more and more web features to its mobile app, and we've just spotted another that's getting ready to make the transition. Google's been showing what us what Gemini can do across all sorts of media, and earlier this year, its ability to work with all things text got a major shot in the arm through the introduction of Canvas. Gemini Canvas makes it easier to work with lengthy documents, generating and editing away, and handling everything from a résumé to some web code. With all that text, it's easy to understand why Canvas may lean a little more towards its browser interface on a PC, but we've already seen developer efforts increasingly target fleshing out the Android side of things. Don't want to miss the best from Android Authority? Set us as a preferred source in Google Search to support us and make sure you never miss our latest exclusive reports, expert analysis, and much more. Looking through version beta of the Google app for Android, we've identified an in-progress change that would bring another Gemini Canvas web feature to the app. Right now with Gemini on the web, you can use Canvas to create things based on the document you're working with. Those include web pages, quizzes, and infographics. In a pinch, you can also do this from the Chrome browser on your phone (leftmost screenshot above), but so far the Gemini app has lacked a native equivalent. With this new release, we're able to preview a not yet publicly accessible change that implements those output options within the Gemini app's UI. We see the same selection of options, just finally now in a place we can access on mobile without jumping through unnecessary hoops. It's anyone's guess when Google might actually push these options live, but doing so seems reasonably straightforward. We'll keep an eye out for any further tweaks to the interface ahead of the feature arriving. ⚠️ An APK teardown helps predict features that may arrive on a service in the future based on work-in-progress code. However, it is possible that such predicted features may not make it to a public release. Follow

Is agentic AI more than hype? This company thinks it knows how to find out
Is agentic AI more than hype? This company thinks it knows how to find out

Fast Company

time2 minutes ago

  • Fast Company

Is agentic AI more than hype? This company thinks it knows how to find out

Over the past five years, advances in AI models' data processing and reasoning capabilities have driven enterprise and industrial developers to pursue larger models and more ambitious benchmarks. Now, with agentic AI emerging as the successor to generative AI, demand for smarter, more nuanced agents is growing. Yet too often 'smart AI' is measured by model size or the volume of its training data. Data analytics and artificial intelligence company Databricks argues that today's AI arms race misses a crucial point: In production, what matters most is not what a model 'knows,' but how it performs when stakeholders rely on it. Jonathan Frankle, chief AI scientist at Databricks, emphasizes that real-world trust and return on investment come from how AI models behave in production, not from how much information they contain. Unlike traditional software, AI models generate probabilistic outputs rather than deterministic ones. 'The only thing you can measure about an AI system is how it behaves. You can't look inside it. There's no equivalent to source code,' Frankle tells Fast Company. He contends that while public benchmarks are useful for gauging general capability, enterprises often over-index on them. What matters far more, he says, is rigorous evaluation on business-specific data to measure quality, refine outputs, and guide reinforcement learning strategies. 'Today, people often deploy agents by writing a prompt, trying a couple of inputs, checking their vibes, and deploying. We would never do that in software—and we shouldn't do it in AI, either,' he says.

How ‘Altman's Pause' could knock the AI industry off course
How ‘Altman's Pause' could knock the AI industry off course

Washington Post

time3 minutes ago

  • Washington Post

How ‘Altman's Pause' could knock the AI industry off course

James Pethokoukis is a senior fellow at the American Enterprise Institute and author of 'The Conservative Futurist.' OpenAI's latest chatbot model, GPT-5, is an improved artificial-intelligence tool: faster, more capable, more accurate. But it's not the technomagic wand some AI optimists hoped for. The leap to 'superintelligence,' the prize behind $400 billion in Big Tech investment this year, now looks later rather than sooner, if even possible. It's not the end of the world if Silicon Valley adjusts its dreams of miracle cures, super-materials and warp-speed growth down toward steady office-automation efficiencies for now. Progress is often uneven, with periods of rapid innovation followed by plateaus in which new technology is incorporated. And tempering our immediate hopes for scientific wonders at least means diminishing our fears of rogue machines and mass job extinction. But this slowdown comes at a dangerous time in which investors are running one step ahead of a populist backlash that could shackle AI with regulation before the technology can reach its next breakthrough. There's now substantial risk that the industry's critics turn the public narrative toward its visible harms — whether it's fears of lost jobs, environmental harm or a broader upheaval of daily life — without enough visible benefits to counteract them. Americans already tell pollsters they are more concerned than excited about AI. Their doomscrolls bring stories of chatbot addiction, celebrity deepfakes and synthetic voices cloning loved ones to scam the elderly. Older generations worry that younger ones are cheating their way through school. Then there are worrisome economic headlines undermining the case for rapid AI progress with minimal government intervention. One example is the squeeze on entry-level tech positions, created by companies' turn to AI for tasks traditionally handled by recent graduates. As summarized by a recent New York Times headline: 'Goodbye, $165,000 Tech Jobs. Student Coders Seek Work at Chipotle.' (Plenty of readers probably texted that link to their college kids.) This disruption is mostly confined to certain tech sectors, but Americans are hearing constant speculation that their white-collar jobs are next, whether or not it's happening anytime soon. As with the China trade shock, limited or exaggerated downsides can dominate perception: Losses in manufacturing towns overshadowed diffuse gains from trade — cheaper goods, greater productivity, new export jobs — and fueled right-wing populism and tariffs. The economy is on shaky ground for reasons unrelated to AI— such as the trade war — and the technology could run into public worries about stagflation. Energy prices are set to rise as consumers compete for power with AI data centers, and the White House is shortsightedly cutting off new projects that might help. Now add the realistic possibility that the AI investment flood, responsible for half of the nation's growth of gross domestic product in the first half of the year, dries up. If the boom busts and drags down the economy, it could merge with job fears into a potent 'disruption without reward' narrative. That would make it far easier for policymakers to impose strict rules, automation taxes or moratoria — stalling AI not because it failed, but because politics killed it. We can see signs of how this might play out now: Trucking unions are pushing to let local governments block Waymo's expansion. Hollywood unions are pressing for strict limits on AI-written scripts and digital replicas. Organized groups protect their turf, while the public, which might enjoy safer transport or cheaper, more varied entertainment, often has little political voice. Should AI fail to deliver tangible benefits for ordinary voters, politicians may be more inclined to acquiesce to the protectionist entreaties of special interests. This echoes economic history. During the Industrial Revolution, Britain's productivity rose while wages stagnated — a period dubbed 'Engels's pause,' after Friedrich Engels's grim account of industrial poverty. Early mechanization spoils went mainly to factory owners, while laborers saw their traditional livelihoods disrupted, sparking the infamous Luddite attacks on textile machinery. Britain's leaders pressed ahead — and later generations reaped enormous prosperity — but the long lag in sharing those gains fueled years of social unrest. Today's version could be 'Altman's pause' in honor of OpenAI boss Sam Altman: Tech giants take most early AI profits, while disrupted workers wait for the promised rising tide to lift all boats. And unlike in the 19th century, modern populist leaders might side with the displaced this time — as Donald Trump did with dockworkers fighting port automation — or with environmentalists alarmed by data centers' water and energy demands. Anti-disruption sentiment is brewing within both progressive and MAGA coalitions, meaning political blowback could come from multiple directions. Engels's pause ended when gains finally spread: New industries created better-paying jobs, skills improved and living standards rose. Governments today should focus on accelerating that diffusion. That means keeping a light touch on regulation, scaling workforce training so algorithms complement rather than replace workers, and ensuring there is reliable and affordable energy — including nuclear — to power AI data centers. Permitting reform should make it easier to build. Sensible safeguards against misuse are essential, but fear should not freeze progress. The aim is to turn any Altman's pause into a short lull before a broad, sustained rise in prosperity.

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store