Latest news with #deepTech
Yahoo
21 hours ago
- Business
- Yahoo
QBTS Stock Gains on Tangible AI Use Cases: More Upside Ahead?
D-Wave Quantum QBTS is accelerating its momentum across both real-world quantum AI applications and deep tech hardware innovation. In terms of application, the company's quantum-enhanced AI is already yielding measurable gains across various domains. Earlier this week, the company's shares jumped following D-Wave's announcement that Japan Tobacco, which leveraged D-Wave's technology for quantum-assisted drug discovery, achieved superior results compared to traditional classical model training. Similarly, the Julich Supercomputing Centre in Germany reported improved accuracy in protein-DNA binding predictions. Added to this, TRIUMF, Canada's national particle accelerator center, demonstrated significant simulation speedups by integrating AI with quantum systems. These early successes validate the practical advantages of combining quantum computing with artificial intelligence. Complementing these use-case achievements is D-Wave's strategic investment in advanced cryogenic packaging, an initial step in scaling both its annealing and gate-model quantum architectures. The company is collaborating with NASA's Jet Propulsion Laboratory (JPL) to develop superconducting bump-bond interconnects, a critical innovation aimed at enhancing the performance and manufacturability of quantum processors. This initiative is expected to unlock multiple hardware advantages, including higher qubit density, extended coherence times and support for multichip quantum processor designs, all essential for progressing toward D-Wave's ambitious 100,000-qubit roadmap. During the first few days of August, shares of D-Wave rallied 6.5% backed by the above developments. Month-to-Date QBTS Share Rally Image Source: Zacks Investment Research Diverging Paths Among Quantum Computing Rivals IonQ IONQ: It is advancing in quantum AI through its gate-based architecture, focusing on hybrid AI model training and partnerships with cloud providers. While strong in developer tooling and quantum machine learning, IonQ is yet to introduce a blockchain framework like QBTS, leaving a potential gap in its emerging markets strategy. Rigetti Computing RGTI: The company remains hardware-focused, prioritizing qubit fidelity and government contracts via its QCS platform. Though exploring AI, Rigetti lacks blockchain-specific initiatives and domain toolkits like D-Wave's PyTorch integration, making its approach more tech-centric and less diversified across emerging commercial applications. Average Target Price for QBTS Suggests Near-Term Upside Based on short-term price targets offered by nine analysts, D-Wave Quantum's average price target represents an increase of 8.7% from the last closing price of $17.18. Image Source: Zacks Investment Research D-Wave Quantum currently carries a Zacks Rank #3 (Hold). You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here. Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report IonQ, Inc. (IONQ) : Free Stock Analysis Report Rigetti Computing, Inc. (RGTI) : Free Stock Analysis Report D-Wave Quantum Inc. (QBTS) : Free Stock Analysis Report This article originally published on Zacks Investment Research ( Zacks Investment Research
Tahawul Tech
2 days ago
- Business
- Tahawul Tech
Interview: VFlowTech CEO believes their technology can meet Middle East renewable energy demands
CNME Editor Mark Forker, sat down with Avishek Kumar, CEO and co-founder of Singaporean-based deep tech company VFlowTech, to learn about the company's expansion plans in the Middle East, and how its unique rugged, rigorous and innovative battery technology can meet the renewable energy demands and decarbonisation targets across the region. Avishek Kumar, is the CEO and co-founder of deep tech company VFlowTech. VFlowTech was established in 2018, and is headquartered in Singapore. The company is on a mission to reinvent long duration energy storage with innovative technologies designed to develop affordable and scalable vanadium redox flow batteries. Under Kumar's fearless leadership and drive the company has enjoyed huge market success in Singapore, and now the plan is to replicate that success in the UAE, and across the Middle East region. The United Arab Emirates is undoubtedly leading the region's clean energy transition, whilst Saudi Arabia has also made no secret around its ambitions to decarbonise. However, with grid instability on the rise, a surge in demand for infrastructure like AI-driven datacentres, which is energy intensive, achieving these decarbonisation targets is challenging. VFlowTech enters the Middle East region off the back of a successful $20.5m funding round. Kumar kickstarted the conversation by highlighting the impact VFlowTech has had in Singapore. 'I have a PhD in solar, and the fact of the matter is when solar became cheap, it became unsustainable, and it was evident that you needed batteries. We developed our technology in Singapore, and Singapore is our primary market. We've been able to successfully deploy our batteries in key use-cases – and we're powering Singapore 24/7 with our battery technology, enabling really long durations and sowing a commercial fibre application on the grid,' said Kumar. Kumar added that the company has a factory in India, and they are engaged in key projects in both the mining and utility industries. Kumar highlighted that the ability of the battery to work in inclement weather conditions is a key market differentiator for them. 'One of the key advantages of our battery is that it can work in incredibly harsh and humid climates. Our battery can operate up to 55-degree ambient, which is a key USP for us as a technology player. Now, anyone that has been following the Middle East marketplace will be aware that the region has seen an unprecedented deployment of renewable energy. Saudi Arabia has announced its ambition to go net-zero, so the deployment of renewable energy is only going to soar and the demand is there. There is an abundance of solar energy, so you will need a lot of batteries, and there has been a big play into lithium-ion technology, but lithium-ion technology has its limitations. You need proper air-conditioning and cooling, so in a harsh climate like the Middle East, lithium-ion technology is limited,' said Kumar. Kumar was quick to point out that VFlowTech has already enjoyed success in the Middle East marketplace. 'Last year, we entered into a partnership with a prominent local company that is looking to provide innovative energy storage solutions in desalination plants, and as we speak, we have our first battery in the KSA. A leading utility in the Middle East has put up a tender for flow batteries, and that is something that we are looking to participate in as well. We are happy that we have anchored many early opportunities in the Middle East,' said Kumar. The conversation then shifted towards the industry verticals VFlowTech is targeting across the Middle East, and outside of renewable energy, utilities and net zero steel are both going to be a key area of focus for the company. 'There are 2-3 key industry verticals for us, but undoubtedly one of them is utilities, and utilities are going to need larger batteries. There have been a number of tenders put out for solar plus batteries which indicates growing demand. We are also looking at net zero steel and steel manufacturing and that's a market where there is growing potential to have solar plus batteries deliver net zero power, so we believe there are a lot of opportunities in the steel manufacturing industry,' said Kumar. The UAE Stargate project has been designed to help the country become a global leader in AI. However, the sheer volume and scale of infrastructure required to power that project is off the scale, but again the datacentre space offers another opportunity for the battery technology produced by VFlowTech. 'We can deliver net zero power to datacentres, and again, this is a space we're focusing on. Saudi Arabia's NEOM project is being built up, but with NEOM there is a huge economy of clean energy, which will require batteries, and our batteries can deliver long-duration cycles. Our batteries can charge in the daytime when there's an abundance of sun, anywhere from 8-10 hours, and then can be charged for 10-12 hours which makes the technology much more suitable for scale,' said Kumar. Kumar added that they have plans to scale manufacturing locally using vanadium. 'We use vanadium, and vanadium is found in petroleum waste, and as we know the Middle East is rich in crude oil. We're also exploring opportunities to partner with a number of local refineries, where we can use the petroleum Sinder to see if there is any vanadium content that we can recover, and that will make localisation possible as the demand rises,' said Kumar. Kumar then highlighted a number of key differentiators that he believes makes vanadium redox flow batteries a much better option that lithium-ion batteries. 'There are multiple factors that contribute to vanadium redox flow batteries outperforming lithium-ion. Typically, a renewable energy plant has a lifetime of 25-30 years, and the lifetime cycle of flow batteries is also 30 years. Vanadium co-exists very effectively with renewable energy. From a safety perspective, there is a fire risk with lithium-ion batteries, and particularly when the temperature gets high the performance degrades significantly. Vanadium redox flow batteries are extremely safe, there is no risk of fire. One other key differentiator for us is performance. Lithium-ion is a good technology, but when it's working in hot and inclement climate conditions then the performance plummets. Ultimately, lithium-ion is not suitable for the Middle East region because of the climate here, it is made possible through advanced cooling technologies, but our technology does not need that advanced cooling technology. In addition to this, 99% of the low component that we use is easily recyclable, and the Middle East doesn't have a lot of lithium, so their local manufacturing content can be high vanadium, so these are all key enablers that make flow batteries more suitable for the Middle East marketplace,' said Kumar. Kumar said the company has engaged in talks with some major players in the energy sector in the Middle East, but explained that with a new technology there always has to be the proof-of-concept phase – but outlined his plans over the next 12 months for their market expansion in the Middle East. 'We have entered into early discussions with a few large independent power producers (IPP) in the region, but these are huge, huge players in the energy industry, so for a new relatively new market entrant like us, we have to work on pilots and proof-of-concepts to put our best foot forward. We have been working with smaller players in Saudi Arabia, and as I mentioned earlier, a prominent utility company has put out tenders for flow batteries, which indicates that they are evaluating technologies. Our approach this year in relation to the Middle East will be to establish an office, somewhere in either Saudi Arabia, or Dubai, build a pipeline, and generally, be much more active in the market. Our initial focus is to first streamline manufacturing because we are a technology leader in this space, and we need to create a supply chain and evolve as a manufacturing company. This year, we are all about execution and once we open an office we can build a pipeline, and when the pipeline is built, we'll explore manufacturing in the Middle East,' said Kumar.
Forbes
15-07-2025
- Health
- Forbes
Rethinking Human-Tech Collaboration With Passive Brain Interfaces
Thorsten O. Zander is the Founder & Chief Scientist at Zander Labs, a deep tech company at the forefront of pBCI and neuroadaptive tech. Recent headlines predict a future of mind-reading machines, but the real breakthrough in brain-computer interfaces (BCIs) isn't about decoding your deepest secrets. It's about building technology that understands, adapts to and evolves with you to enable a new era of human-centric innovation. The question is not what machines can take from us, but how they can learn from us to create technology that is fundamentally more responsive, supportive and empowering. The Cognitive Revolution Traditional BCIs require users to learn artificial machine languages, training their minds to issue specific, often awkward commands. In contrast, passive BCIs represent a paradigm shift. As I've written about previously, passive BCIs use sensors to record brain activity and translate these signals into digital data. This removes the need for surgery, and it also allows AI to evaluate real-time information about users' emotions. Rather than demanding that humans adapt to machines, we should build systems that adapt to us, silently interpreting patterns in brain activity like attention, workload or fatigue. This isn't science fiction—this is neuroadaptive technology, and it's happening now. It's a philosophical shift in human-machine collaboration. Rather than training humans to think in machine-readable patterns, we should build machines that learn from how humans naturally think. Precision Insights: A Transformative Opportunity Consider some of the practical applications of passive BCIs. With nuanced, real-time insights into attention, focus and emotional state, this technology could enable empathetic AI. Unlike what speculative mind-reading headlines suggest, these systems offer opportunities to enable practical, ethical advances across healthcare, education, workplace productivity and accessibility. Instead of developing AI models for predicting what you want, the goal could be to adapt to real needs, context and values, resulting in a fundamentally more personal and supportive experience. For example, the technology could tell when someone is overloaded and adapt to reduce stress. This could lead to learning platforms recognizing cognitive fatigue and offering support or communication tools that adjust for individuals with physical limitations. The Privacy Imperative As technology gains the ability to detect subtle cognitive states, privacy and user agency move to the forefront of innovation. The brain data collected today is already deeply personal, offering insights into not just what we're doing, but how our brains are functioning across a growing number of classifiers. Who owns your brain data? How can we ensure it's used ethically? What safeguards must be in place before these technologies become mainstream? These aren't abstract concerns for some distant future—they're immediate challenges requiring solutions now. That's why the future of neuroadaptive technology is systems that process data locally whenever possible, encrypt all signals and ensure users retain full control over their information. The goal is not surveillance but support that makes accurate insights possible while protecting what makes us human. Bridging The Gap One persistent challenge for brain-computer interfaces—especially passive BCIs—has been bridging the gap between impressive lab results and real-world, user-centered solutions. The field has been caught between academic explorations lacking real-world applicability and consumer gadgets lacking scientific rigor. Challenges with passive BCIs aren't just the tech. It's also about building something people actually want to use. Privacy matters enormously when you're dealing with brain data, but obsessing over perfect safeguards before we even have working systems misses the point. The technical hurdles are solvable. Signal noise and reliability issues just mean we need better real-world engineering. We should focus on applications where passive BCIs offer clear advantages: better safety monitoring, enhanced accessibility or cognitive support that traditional interfaces can't match. Success in these specific areas will build the trust and evidence base that broader adoption requires. The path forward requires technology that is scientifically valid and practically useful, delivering solutions that provide meaningful insights without the complexity of traditional research-grade equipment. Early adoption doesn't require perfect technology. It requires technology that solves specific problems better than existing alternatives. The first mainstream passive BCI and neuroadaptive tech successes will come from focusing on where these systems can uniquely improve safety, productivity or accessibility—setting the stage for wider transformation. Technology For The People As we pursue these advances, we must remember that the goal isn't technology for its own sake, but truly context-aware technology that understands and supports people more effectively. This means designing with empathy, testing with diverse populations and asking whether our innovations are making lives meaningfully better. As AI moves into an increasingly dominant position in our lives, BCI technology offers something unique: a direct connection to human intelligence. Rather than replacing human thinking, it amplifies our natural cognitive abilities and helps machines better understand human needs. The true measure of progress in brain-computer interfaces will be how well we translate neural signals into meaningful insights that enrich lives and expand human potential. Our task is to build technology that learns from and adapts to us, never the other way around. The future of BCI is about connecting human potential with technological possibility. This is not the age of mind-reading. It's the age of mind-understanding, where technology is guided by the remarkable complexity of the human mind. Let's ensure that the future is built on science, empathy and trust. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
16-06-2025
- Business
- Forbes
How AI And Permanent Capital Are Reshaping Private Markets
Pierrick Bouffaron, Operating Partner for Entropia Capital , a global investor in technology with offices in Hong Kong, Luxembourg and NYC. getty A quiet yet profound transformation is reshaping private equity and late-stage venture capital: the convergence of AI, operational value creation and long-hold ownership models. At the core of this evolution are AI-fueled roll-up strategies and the rise of permanent capital vehicles, both of which appear to be increasingly favored by firms ready to move beyond the rigid timelines of traditional fund cycles. We are entering a new era where algorithmic leverage, not just capital, is driving the next wave of scalable, operational value creation. Over the past decade, I've worked at the intersection of deep tech investing, corporate innovation and startup acceleration, advising and co-building technology ventures across the U.S., Europe and Southeast Asia. I've seen firsthand how data infrastructure and operational control are becoming essential tools for private market outperformance. Roll-ups, where investors acquire and consolidate smaller businesses in fragmented sectors, have long been a private equity favorite. They can deliver efficiencies through scale, help negotiate better contracts, centralize functions and ultimately allow the group to be sold at a premium. But executing a roll-up is hard. It requires deep market knowledge, relentless due diligence and seamless post-deal integration. That's where AI is rewriting the playbook. Modern AI systems can crawl thousands of databases, parse regulatory filings and analyze web content to surface ideal acquisition targets using natural language processing. Machine learning models can flag customer churn risk, uncover margin levers and benchmark operational key performance before a term sheet is signed. After closing, AI can help facilitate faster onboarding, workflow automation, supply chain optimization and digital transformation across units. This is no longer theory. Thrive Capital, an investor behind OpenAI and Stripe, has been fundraising for Thrive Holdings, a $1 billion permanent capital vehicle to acquire and operate 'everyday' businesses, including homeowner associations and accounting firms, with AI as the operational backbone. The idea is to use algorithms and automation to drive improvements in margins and service across legacy sectors. And Thrive isn't an outlier. This playbook builds on a proven model seen in industries like dental chains and plumbing services: Standardize systems, share overhead and scale intelligently. What's new is that the engine now runs on code. The Acceleration Of AI In Private Equity AI in private markets may seem recent, but the data revolution has been gaining steam for decades. In the early 2000s, quantitative hedge funds like Renaissance Technologies led the way (paywall). Private equity generally followed with caution until firms like Two Six Capital began using data science to evaluate portfolio companies. Two Six participated in more than $27 billion worth of deals using these analytics. The pace accelerated in the 2020s, with some studies indicating that firms investing in data science capabilities outperformed their peers (paywall), highlighting a link between analytics and business success. One example is Paris-based Jolt Capital, which developed an AI platform that's been in use since 2016, according to the platform's website. It scans the web to spot under-the-radar investment opportunities in tech firms. It tracks patent filings, executive shifts, market sentiment and financial signals, which can offer an edge in sourcing and diligence, particularly in Europe's fragmented deep tech landscape. Another example is EQT, also in Europe, which uses its internal AI engine, Motherbrain, to help source investments. Shaping Long-Term Plays The other major trend I'm seeing reshape private markets is the rise of permanent capital vehicles (PCVs), investment structures without fixed exit deadlines. In my view, their popularity is likely increasing thanks to their compatibility with operationally intensive strategies like AI-led roll-ups. Traditional funds must return capital in seven to 10 years, in my experience. PCVs allow firms to take the long view, reinvest gains and build durable, cash-generating businesses over decades. It's a model tailor-made for transformations that take time, like deploying AI across dozens of acquired companies. Sequoia Capital helped pioneer this approach (paywall) in 2021 by launching The Sequoia Fund, a structure designed to hold public stocks indefinitely. Instead of being forced to exit positions in winners after an initial public offering, Sequoia now retains long-term upside and strategic optionality. Andreessen Horowitz took a similar approach in 2023 with its a16z Perennial Venture Capital Fund. No public tally exists for how many firms run PCVs, but I'm seeing the trend accelerating. From my observations, top-tier firms with operational muscle and AI ambitions are increasingly choosing flexible timelines over forced exits. Capital Meets Code: A Strategic Convergence Together, AI-powered roll-ups and permanent capital vehicles signal a structural shift in how investment firms deploy capital and build value. I believe the boundary between late-stage venture and traditional private equity is fading, as operational control becomes the new priority. Firms are hiring engineers as core team members, building proprietary tooling and behaving less like investors and more like operators. A new class of fund is emerging: They aggregate assets, standardize them with AI and create long-term cash flow engines. To me, this means the competitive edge is increasingly found in the data stack. This isn't a tactical update; it's a redefinition of what happens after the deal closes. For other firms looking to adapt to these shifts, start by embedding technical talent—such as data scientists, machine learning engineers and AI product leads—into your core deal and operations teams. Second, consider piloting internal tools that can track portfolio performance, not only financially but also operationally, and layer in data streams that surface risks and opportunities in real time. I believe those who adapt could not only see better internal rates of return but also build a compounding, self-improving edge that defines the next generation of value creation. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Japan Times
18-05-2025
- Business
- Japan Times
Government capital is not just 'silly money'
Silicon Valley-minded venture capitalists (VCs) around the world tend to blindly criticize government capital for innovation as 'silly money.' For sure, there has been a global trend to replicate concepts from Silicon Valley with regards to the 'power law' of venture capital, 'move fast, break things' disruption, avoidance of government and the 'fake it until you make it' confidence, among others. Nothing could be more wrong — especially when Silicon Valley is fundamentally a sui generis culture and ecosystem. Unlike Silicon Valley's predominantly private-sector-driven ecosystem, many Asian societies exhibit greater risk aversion, necessitating proactive government involvement to stimulate entrepreneurial activity. Historically, government funding and industrial policy have played a pivotal role in fostering innovation and supporting startups across Asia, starting with Japan, followed by other countries like South Korea, Singapore and Taiwan, among others. And we must not forget that, even in the establishment of the Silicon Valley ecosystem, the U.S. government and military played a big role in the postwar years and the military even laid the foundation for the invention of the internet and the semiconductor chip. In particular, the commercialization of cutting-edge fundamental research at universities carries high risks and very long gestation periods that could be unpalatable to private-sector players. Further, deep-tech and life-science research from universities are often of strategic interest to governments, particularly from the angles of national security and economic development, which typical investors may not be attracted to. Indeed, government-backed VCs, including public university VCs are more inclined to invest in early-stage companies, particularly those emerging from academic or research institutions. On the other hand, independent VCs tend to focus on later-stage investments where the risk is lower and the potential for returns is clearer. This approach often leads to underinvestment in nascent technologies and startups that require more time and support to mature. A study by Iqbal Muhammad and Stephanie Serve analyzing 3,817 firms across nine Asian developing countries from 1991 to 2017 found that government-backed startups were more likely to receive early-stage financing compared to those backed by independent VC firms. And while government-backed VCs may have a lower likelihood of successful exits compared with independent VCs, which tend to follow more rigorous due diligence processes and market-driven strategies, government-backed startups perform better in the expansion and later stages thanks to early investments aimed at unlocking exponential innovation. As examples across Asia, Singapore's government actively supports startups through initiatives like the Startup SG Equity program. Last year, an additional $338 million was allocated to this program, increasing the investment cap per startup from $6 million to $9 million. Taiwan's government has invested approximately $211.6 million over five years to support local equipment and materials suppliers in building research and development capabilities. Meanwhile, mainland China exemplifies a robust government-led approach to innovation. In 2022, tax rebates for corporate R&D reached 1.3 trillion Chinese yuan (approximately $180 billion), marking a 28.8% annual growth rate since 2018. Additionally, in 2025, China launched a 1 trillion yuan ($138 billion) government-backed venture fund targeting emerging technologies like quantum computing and artificial intelligence. With this context, a key platform to commercialize fundamental research — especially from universities and research institutions — are government-backed university VCs and incubation programs. In the early stage deep-tech space, incubators turn basic research into commercializable ideas and found companies, while university VCs would invest when startups at the seed stage are ready to create products based on their intellectual property and beyond. In 2022, the Japanese government launched the University Fund of Japan, a ¥10 trillion ($68.5 billion) endowment aimed at revitalizing the nation's research capabilities and fostering innovation. This initiative addresses concerns over declining research performance and aims to position Japanese universities as global leaders in scientific research. Profits from the investments are distributed to selected universities, with a maximum annual allocation of ¥300 billion ($2 billion). The duration is suitably long for early stage deep-tech investments — the support is structured to continue for up to 25 years, providing long-term financial stability to recipient institutions. Universities are chosen based on their strategies for research excellence and organizational reform. Tohoku University was the first institution selected under this program. Public university VCs like Kyoto-iCAP (Kyoto University Innovation Capital), where the author works, are also designed to take high risks to commercialize fundamental university research through government funding alongside private-sector limited partners. Its funds, with a capital size of more than $220 million, have a duration of 12 to 15 years to reflect the high risks and long gestation periods. Indeed, according to Global University Venturing, Japan has one of the most advanced university VC ecosystems in Asia — 85% of its top universities have an investment vehicle to support its startups. Other notable Japanese university VCs are University of Tokyo Edge Capital Partners (UTEC) — which leads the pack with an approximate capital size of $594 million, University of Tokyo Innovation Platform, Osaka University Venture Capital and Tohoku University Venture Partners. More than 40% of European institutions and more than half of Australian campuses have funds too. In contrast, only about a third of U.S. universities maintain such investment vehicles, which goes back to the U.S. and Silicon Valley having a unique private-sector-dominated ecosystem that is backed by a highly entrepreneurial and risk-taking culture. Some of the successful exits that have emerged from the university VC ecosystem are Kyoto iCAP-funded Cuorips and Chordia Therapeutics, UTEC-funded PeptiDream and Spiber, National University of Singapore-incubated and Temasek-backed VC fund Vertex-funded PatSnap and Oxford Science Enterprises-backed Oxford Nanopore Technologies and Immunocore. Going forward, especially when deep-tech fields like semiconductors, materials, clean energy, AI and life sciences become more strategically important for Asian societies, further funding from governments and universities are crucial. This can eventually scale the early stage of a deep-tech startup ecosystem and encourage risk-sharing that could attract more private-sector players. Raymond Woo is the Singapore Office Representative of Kyoto-iCAP (Kyoto University Innovation Capital), Kyoto University's venture capital firm.
