Latest news with #quantumAI
Forbes
7 days ago
- Business
- Forbes
Doing The Work With Frontier Models: I'll Talk To AI
Artificial Intelligence processor unit. Powerful Quantum AI component on PCB motherboard with data ... More transfers. Within the industry, where people talk about the specifics of how LLMs work, they often use the term 'frontier models.' But if you're not connected to this business, you probably don't really know what that means. You can intuitively apply the word 'frontier' to know that these are the biggest and best new systems that companies are pushing. Another way to describe frontier models is as 'cutting-edge' AI systems that are broad in purpose, and overall frameworks for improving AI capabilities. When asked, ChatGPT gives us three criteria – massive data sets, compute resources, and sophisticated architectures. Here are some key characteristics of frontier models to help you flush out your vision of how these models work: First, there is multimodality, where frontier models are likely to support non-text inputs and outputs – things like image, video or audio. Otherwise, they can see and hear – not just read and write. Another major characteristic is zero-shot learning, where the system is more capable with less prompting. And then there's that agent-like behavior that has people talking about the era of 'agentic AI.' If you want to play 'name that model' and get specific about what companies are moving this research forward, you could say that GPT 4o from OpenAI represents one such frontier model, with multi-modality and real-time inference. Or you could tout the capabilities of Gemini 1.5, which is also multimodal, with decent context. And you can point to any number of other examples of companies doing this kind of research well…but also: what about digging into the build of these systems? At a recent panel at Imagination in Action, a team of experts analyzed what it takes to work in this part of the AI space and create these frontier models The panel moderator, Peter Grabowski, introduced two related concepts for frontier models – quality versus sufficiency, and multimodality. 'We've seen a lot of work in text models,' he said. 'We've seen a lot of work on image models. We've seen some work in video, or images, but you can easily imagine, this is just the start of what's to come.' Douwe Kiela, CEO of Contextual AI, pointed out that frontier models need a lot of resources, noting that 'AI is a very resource-intensive endeavor.' 'I see the cost versus quality as the frontier, and the models that actually just need to be trained on specific data, but actually the robustness of the model is there,' said Lisa Dolan, managing director of Link Ventures (I am also affiliated with Link.) 'I think there's still a lot of headroom for growth on the performance side of things,' said Vedant Agrawal, VP of Premji Invest. Agrawal also talked about the value of using non-proprietary base models. 'We can take base models that other people have trained, and then make them a lot better,' he said. 'So we're really focused on all the all the components that make up these systems, and how do we (work with) them within their little categories?' The panel also discussed benchmarking as a way to measure these frontier systems. 'Benchmarking is an interesting question, because it is single-handedly the best thing and the worst thing in the world of research,' he said. 'I think it's a good thing because everyone knows the goal posts and what they're trying to work towards, and it's a bad thing because you can easily game the system.' How does that 'gaming the system' work? Agrawal suggested that it can be hard to really use benchmarks in a concrete way. 'For someone who's not deep in the research field, it's very hard to look at a benchmarking table and say, 'Okay, you scored 99.4 versus someone else scored 99.2,'' he said. 'It's very hard to contextualize what that .2% difference really means in the real world.' 'We look at the benchmarks, because we kind of have to report on them, but there's massive benchmark fatigue, so nobody even believes it,' Dolan said. Later, there was some talk about 10x systems, and some approaches to collecting and using data: · Identifying contractual business data · Using synthetic data · Teams of annotators When asked about the future of these systems, the panel return these three concepts: · AI agents · Cross-disciplinary techniques · Non-transformer architectures Watch the video to get the rest of the panel's remarks about frontier builds. What Frontier Interfaces Will Look Like Here's a neat little addition – interested in how we will interact with these frontier models in 10 years' time, I put the question to ChatGPT. Here's some of what I got: 'You won't 'open' an app—they'll exist as ubiquitous background agents, responding to voice, gaze, emotion, or task cues … your AI knows you're in a meeting, it reads your emotional state, hears what's being said, and prepares a summary + next actions—before you ask.' That combines two aspects, the mode, and the feel of what new systems are likely to be like. This goes back to the personal approach where we start seeing these models more as colleagues and conversational partners, and less as something that stares at you from a computer screen. In other words, the days of PC-DOS command line systems are over. Windows changed the computer interface from a single-line monochrome system, to something vibrant with colorful windows, reframing, and a tool-based desktop approach. Frontier models are going to do even more for our sense of interface progression. And that's going to be big. Stay tuned.
Yahoo
12-06-2025
- Business
- Yahoo
Multiverse Computing Raises $215M to Scale Ground-Breaking Technology that Compresses LLMs by up to 95%
Technology breakthrough attracts international investment. Quantum AI leader to turbo charge AI proliferation, reduce power concerns and bring the technology to the edge Multiverse Computing's Founding Team SAN SEBASTIAN, Spain , June 12, 2025 (GLOBE NEWSWIRE) -- Multiverse Computing, the global leader in quantum-inspired AI model compression, has developed CompactifAI, a compression technology capable of reducing the size of LLMs (Large Language Models) by up to 95% while maintaining model performance. Having spent 2024 developing the technology and rolling it out to initial customers, the company today announces a €189 million ($215 million) investment round. The Series B will be led by Bullhound Capital with the support of world-class investors such as HP Tech Ventures, SETT, Forgepoint Capital International, CDP Venture Capital, Santander Climate VC, Quantonation, Toshiba and Capital Riesgo de Euskadi - Grupo SPRI. The company has brought on widespread support for this push with a range of international and strategic investors. The investment will accelerate widespread adoption to address the massive costs prohibiting the roll out of LLMs, revolutionizing the $106 billion AI inference market. LLMs typically run on specialized, cloud-based infrastructure that drives up data center costs. Traditional compression techniques—quantization and pruning—aim to address these challenges, but their resulting models significantly underperform original LLMs. With the development of CompactifAI, Multiverse discovered a new approach. CompactifAI models are highly-compressed versions of leading open source LLMs that retain original accuracy, are 4x-12x faster and yield a 50%-80% reduction in inference costs. These compressed, affordable, energy-efficient models can run on the cloud, on private data centers or—in the case of ultra compressed LLMs—directly on devices such as PCs, phones, cars, drones and even Raspberry Pi. 'The prevailing wisdom is that shrinking LLMs comes at a cost. Multiverse is changing that,' said Enrique Lizaso Olmos, Founder and CEO of Multiverse Computing. 'What started as a breakthrough in model compression quickly proved transformative—unlocking new efficiencies in AI deployment and earning rapid adoption for its ability to radically reduce the hardware requirements for running AI models. With a unique syndicate of expert and strategic global investors on board and Bullhound Capital as lead investor, we can now further advance our laser-focused delivery of compressed AI models that offer outstanding performance with minimal infrastructure.' CompactifAI was created using Tensor Networks, a quantum-inspired approach to simplifying neural networks. Tensor Networks is a specialized field of study pioneered by Román Orús, Co-Founder and Chief Scientific Officer at Multiverse. 'For the first time in history, we are able to profile the inner workings of a neural network to eliminate billions of spurious correlations to truly optimize all sorts of AI models,' said Orús. Compressed versions of top Llama, DeepSeek and Mistral models are available now, with additional models coming soon. Per Roman, Co-founder & Managing Partner, Bullhound Capital, said: 'Multiverse's CompactifAI introduces material changes to AI processing that address the global need for greater efficiency in AI, and their ingenuity is accelerating European sovereignty. Román Orús has convinced us that he and his team of engineers are developing truly world-class solutions in this highly complex and compute intensive field. Enrique Lizaso is the perfect CEO for rapidly expanding the business in a global race for AI dominance. I am also pleased to see that so many high-profile investors such as HP and Forgepoint decided to join the round. We welcome their participation.' Tuan Tran, President of Technology and Innovation, HP Inc., commented: 'At HP, we are dedicated to leading the future of work by providing solutions that drive business growth and enhance professional fulfillment. Our investment in Multiverse Computing supports this ambition. By making AI applications more accessible at the edge, Multiverse's innovative approach has the potential to bring AI benefits of enhanced performance, personalization, privacy and cost efficiency to life for companies of any size.' Damien Henault, Managing Director, Forgepoint Capital International, said: 'The Multiverse team has solved a deeply complex problem with sweeping implications. The company is well-positioned to be a foundational layer of the AI infrastructure stack. Multiverse represents a quantum leap for the global deployment and application of AI models, enabling smarter, cheaper and greener AI. This is only just the beginning of a massive market opportunity.' Multiverse Computing extends its sincere gratitude to its current investors for their continued trust and support, as well as to the European institutions whose backing has been instrumental in achieving this milestone. For more information about Multiverse Computing and CompactifAI, visit About Multiverse Computing Multiverse Computing is the leader in quantum-inspired AI model compression. The company's deep expertise in quantum software and AI led to the development of CompactifAI, a revolutionary AI model compressor. CompactifAI compresses LLMs by up to 95% with only 2-3% precision loss. CompactifAI models reduce computing requirements and unleash new use cases for AI across industries. Multiverse Computing is headquartered in Donostia, Spain, with offices across Europe, the US, and Canada. The company won DigitalEurope's 2024 Future Unicorn award and was recognized by CB Insights as one of the Top 100 Most Promising AI Companies in 2025. With over 160 patents and 100 customers globally, including Iberdrola, Bosch, and the Bank of Canada, Multiverse Computing has raised c.$250M to date. For more information, visit About Bullhound Capital Bullhound Capital is the investment management arm of GP Bullhound, building with founders creating category-leading technology companies. Launched in 2008 with over €1 billion deployed, it has invested in global leaders like Spotify, Klarna, Revolut, Slack, Unity, ConnexAI and EcoVadis. Operating from 13 offices worldwide, its platform delivers hands-on, founder-focused support across strategy, growth, and execution. From quantum to entertainment, Bullhound Capital backs global leaders applying Artificial Intelligence to solve real-world problems. About SETT The Sociedad Española para la Transformación Tecnológica, Entidad Pública Empresarial, SETT, attached to the Ministry for Digital Transformation and Public Function, is a public entity dedicated to the financing and promotion of advanced and transformative digital technologies. The operation is carried out through the Next Tech fund, whose objective is to encourage private investment and improve access to financing in strategic Spanish sectors such as disruptive technologies. The implementation of the Next Tech, foreseen in the Recovery, Transformation and Resilience Plan, is among the functions of SETT, which also manages two other financial instruments to boost the technological business ecosystem: PERTE Chip, dedicated to microelectronics and semiconductors, and Spain Audiovisual Hub, which promotes the digitization of the audiovisual sector. Contact InformationLaunchSquad for Multiverse Computingmultiverse@ A photo accompanying this announcement is available at in to access your portfolio
Yahoo
12-06-2025
- Business
- Yahoo
Multiverse Computing Raises $215M to Scale Ground-Breaking Technology that Compresses LLMs by up to 95%
Technology breakthrough attracts international investment. Quantum AI leader to turbo charge AI proliferation, reduce power concerns and bring the technology to the edge Multiverse Computing's Founding Team SAN SEBASTIAN, Spain , June 12, 2025 (GLOBE NEWSWIRE) -- Multiverse Computing, the global leader in quantum-inspired AI model compression, has developed CompactifAI, a compression technology capable of reducing the size of LLMs (Large Language Models) by up to 95% while maintaining model performance. Having spent 2024 developing the technology and rolling it out to initial customers, the company today announces a €189 million ($215 million) investment round. The Series B will be led by Bullhound Capital with the support of world-class investors such as HP Tech Ventures, SETT, Forgepoint Capital International, CDP Venture Capital, Santander Climate VC, Quantonation, Toshiba and Capital Riesgo de Euskadi - Grupo SPRI. The company has brought on widespread support for this push with a range of international and strategic investors. The investment will accelerate widespread adoption to address the massive costs prohibiting the roll out of LLMs, revolutionizing the $106 billion AI inference market. LLMs typically run on specialized, cloud-based infrastructure that drives up data center costs. Traditional compression techniques—quantization and pruning—aim to address these challenges, but their resulting models significantly underperform original LLMs. With the development of CompactifAI, Multiverse discovered a new approach. CompactifAI models are highly-compressed versions of leading open source LLMs that retain original accuracy, are 4x-12x faster and yield a 50%-80% reduction in inference costs. These compressed, affordable, energy-efficient models can run on the cloud, on private data centers or—in the case of ultra compressed LLMs—directly on devices such as PCs, phones, cars, drones and even Raspberry Pi. 'The prevailing wisdom is that shrinking LLMs comes at a cost. Multiverse is changing that,' said Enrique Lizaso Olmos, Founder and CEO of Multiverse Computing. 'What started as a breakthrough in model compression quickly proved transformative—unlocking new efficiencies in AI deployment and earning rapid adoption for its ability to radically reduce the hardware requirements for running AI models. With a unique syndicate of expert and strategic global investors on board and Bullhound Capital as lead investor, we can now further advance our laser-focused delivery of compressed AI models that offer outstanding performance with minimal infrastructure.' CompactifAI was created using Tensor Networks, a quantum-inspired approach to simplifying neural networks. Tensor Networks is a specialized field of study pioneered by Román Orús, Co-Founder and Chief Scientific Officer at Multiverse. 'For the first time in history, we are able to profile the inner workings of a neural network to eliminate billions of spurious correlations to truly optimize all sorts of AI models,' said Orús. Compressed versions of top Llama, DeepSeek and Mistral models are available now, with additional models coming soon. Per Roman, Co-founder & Managing Partner, Bullhound Capital, said: 'Multiverse's CompactifAI introduces material changes to AI processing that address the global need for greater efficiency in AI, and their ingenuity is accelerating European sovereignty. Román Orús has convinced us that he and his team of engineers are developing truly world-class solutions in this highly complex and compute intensive field. Enrique Lizaso is the perfect CEO for rapidly expanding the business in a global race for AI dominance. I am also pleased to see that so many high-profile investors such as HP and Forgepoint decided to join the round. We welcome their participation.' Tuan Tran, President of Technology and Innovation, HP Inc., commented: 'At HP, we are dedicated to leading the future of work by providing solutions that drive business growth and enhance professional fulfillment. Our investment in Multiverse Computing supports this ambition. By making AI applications more accessible at the edge, Multiverse's innovative approach has the potential to bring AI benefits of enhanced performance, personalization, privacy and cost efficiency to life for companies of any size.' Damien Henault, Managing Director, Forgepoint Capital International, said: 'The Multiverse team has solved a deeply complex problem with sweeping implications. The company is well-positioned to be a foundational layer of the AI infrastructure stack. Multiverse represents a quantum leap for the global deployment and application of AI models, enabling smarter, cheaper and greener AI. This is only just the beginning of a massive market opportunity.' Multiverse Computing extends its sincere gratitude to its current investors for their continued trust and support, as well as to the European institutions whose backing has been instrumental in achieving this milestone. For more information about Multiverse Computing and CompactifAI, visit About Multiverse Computing Multiverse Computing is the leader in quantum-inspired AI model compression. The company's deep expertise in quantum software and AI led to the development of CompactifAI, a revolutionary AI model compressor. CompactifAI compresses LLMs by up to 95% with only 2-3% precision loss. CompactifAI models reduce computing requirements and unleash new use cases for AI across industries. Multiverse Computing is headquartered in Donostia, Spain, with offices across Europe, the US, and Canada. The company won DigitalEurope's 2024 Future Unicorn award and was recognized by CB Insights as one of the Top 100 Most Promising AI Companies in 2025. With over 160 patents and 100 customers globally, including Iberdrola, Bosch, and the Bank of Canada, Multiverse Computing has raised c.$250M to date. For more information, visit About Bullhound Capital Bullhound Capital is the investment management arm of GP Bullhound, building with founders creating category-leading technology companies. Launched in 2008 with over €1 billion deployed, it has invested in global leaders like Spotify, Klarna, Revolut, Slack, Unity, ConnexAI and EcoVadis. Operating from 13 offices worldwide, its platform delivers hands-on, founder-focused support across strategy, growth, and execution. From quantum to entertainment, Bullhound Capital backs global leaders applying Artificial Intelligence to solve real-world problems. About SETT The Sociedad Española para la Transformación Tecnológica, Entidad Pública Empresarial, SETT, attached to the Ministry for Digital Transformation and Public Function, is a public entity dedicated to the financing and promotion of advanced and transformative digital technologies. The operation is carried out through the Next Tech fund, whose objective is to encourage private investment and improve access to financing in strategic Spanish sectors such as disruptive technologies. The implementation of the Next Tech, foreseen in the Recovery, Transformation and Resilience Plan, is among the functions of SETT, which also manages two other financial instruments to boost the technological business ecosystem: PERTE Chip, dedicated to microelectronics and semiconductors, and Spain Audiovisual Hub, which promotes the digitization of the audiovisual sector. Contact InformationLaunchSquad for Multiverse Computingmultiverse@ A photo accompanying this announcement is available at
Yahoo
12-05-2025
- Business
- Yahoo
Quantum AI is becoming a popular interest for many businesses
When you buy through links on our articles, Future and its syndication partners may earn a commission. Three in five businesses are exploring quantum AI Data analytics and machine learning is a key application for the tech High costs and lacking knowledge and skills are barriers to full adoption Businesses are more familiar with quantum AI than you might expect, with more then three in five actively investing in or exploring the technology, new research has claimed. A report from SAS has revealed how the technology's most popular application is in data analytics and machine learning (48%), with research and development a fairly close second (41%) and cybersecurity in third place (35%). Supple chain and logistics (31%), finance and risk management (26%) and marketing (20%) are also areas that are being explored for the use of quantum AI. The company noted 'quantum AI' is the combination of AI as we know it today with the power of quantum computing, enabling the development of new algorithms, models and other systems that can process complex data, train complicated ML models and solve problems that would otherwise be considered highly challenging or impossible with today's tech. However, the usual barriers apply as per any new technology, with high costs (38%), a lack of knowledge or understanding (35%), uncertainty about real-world use cases (31%), a lack of trained workers (31%) and a lack of regulatory guidelines (26%) all preventing businesses from being able to or wanting to explore quantum AI in more detail. SAS even acknowledged that there's a lot of hype around quantum computing and quantum AI, adding that today's research into the topic can be confusing. "With the emergence of quantum technologies, companies can analyse more data than ever and achieve amazingly fast answers to very complex questions involving myriad variables," SAS Principal Quantum Architect Bill Wisotsky explained. Although many argue that quantum AI use cases could still be years – or even decades – off, today's research is paving the way and many enterprises are already starting to explore the emerging technology's applications now. Among the key industries set to benefit from quantum AI include life sciences for drug discovery, financial services for risk management, and manufacturing for optimized processes. These are the best AI tools and best AI writers Access today's most powerful chips with the best cloud computing services Microsoft makes major quantum computing breakthrough — development of most stable qubits might actually make the technology viable for many, but will anyone be able to afford it? Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
