Advancements in AI and quantum computing are driving this growth, helping these platforms reach high enough accuracy levels to replace physical trials and rival traditional lab methods, while operating at a fraction of the cost and time.

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AI continues to dominate, capturing 50% of venture investment. At the same time, investors are doubling down on hard tech — hardware-focused and capital-intensive technology — driven by surging energy demands from AI, advancements in robotics, and growing defense interest.

Below, we break down the top stories from this quarter’s report, including:

• Funding tops $90B for the third straight quarter, while deal count declines
• Hard tech claims 6 of the top 10 largest deals
• AI companies command funding premiums across sectors
• Regulatory shifts push big tech from M&A to minority investments
• CVC deals hit a 7-year low as the tariff threat looms

We also outline the categories shaping venture dealmaking for the rest of 2025 — including stablecoins, defense tech, quantum, and nuclear energy.

Let’s dive in.

Download the full report to access comprehensive data and charts on the evolving state of venture across sectors, geographies, and more.

Top stories in Q2’25

1. Funding tops $90B for the third straight quarter, while deal count declines

Venture funding reached $94.6B in Q2’25, marking the second-highest quarterly figure since Q2’22 and the third straight quarter to surpass $90B.

While funding dipped slightly from Q1’25, the decline reflects normalization after OpenAI’s $40B raise inflated numbers in Q1. In fact, Q2 remained elevated even as foundation model developers accounted for just 3% of total capital, down from 36% in Q1’25 and 29% in Q4’24. This shift signals a broadening of venture activity beyond foundation models into the broader AI ecosystem and adjacent hard tech sectors.

With this continued momentum, annual funding is projected to reach nearly $440B, a 53% increase from 2024, pointing to a sustained recovery in venture investment.

At the same time, deal volume continues to decline, reflecting greater investor selectivity. Q2 saw just 6,028 deals — the lowest quarterly total since Q4’16. This puts 2025 on pace for around 25,000 deals, or nearly half the volume seen in 2022, even as total funding approaches similar levels.

While investors are pulling back on the number of deals, they’re deploying more capital per investment: the median deal size hit a new high of $3.5M in 2025 YTD. Rising check sizes and falling deal count underscore a shift toward fewer, higher-conviction bets.

2. Hard tech claims 6 of the top 10 largest deals

Six of the 10 largest deals in Q2’25 went to hard tech companies, which are firms building capital-intensive physical products.

CBI customers: Track the highest funding startups in Q2’25

This surge is driven by macro forces such as onshoring initiatives, clean energy investment, and the rise of physical AI, which is enabling new capabilities across robotics, autonomy, and industrial systems.

Mega-rounds ($100M+ deals) spanned multiple sectors:

• Montera Infrastructure: $1.5B for hyperscale data center solutions
• Commonwealth Fusion Systems: $800M for commercial nuclear fusion
• Neuralink: $650M for brain-computer interfaces

Geopolitical tensions are also pushing capital toward defense, where startups are securing large rounds:

• World View: $2.6B for high-altitude aerospace platforms
• Anduril: $2.5B for autonomous defense systems and defense connectivity platforms
• Helsing: $693M for AI-powered defense applications

Across the board, defense tech startups are now commanding a median revenue multiple of 17.4x, edging out AI companies at 17.1x and all other major sectors. This signals high investor confidence and competition, driving premium valuations across the defense tech sector.

With investor appetite moving toward physical infrastructure and embodied AI, the rise of hard tech represents a shift likely to define the next chapter of venture investing.

3. AI companies command funding premiums across sectors

The venture market is experiencing a pronounced “AI premium,” with median deal size for AI companies reaching $4.6M in 2025 — over $1M more than the broader market. 

But the premium isn’t just financial. AI companies also score higher on CB Insights’ Mosaic Score (success probability) and Commercial Maturity (ability to compete and partner) across most sectors, signaling stronger fundamentals and market readiness in the eyes of investors.

AI companies in auto tech — with most focused on autonomous driving — are commanding the highest premium. Their median deal size is $20.6M higher than non-AI auto tech peers, and their average Mosaic score is 99 points greater. This quarter, the largest AI auto tech deal went to Applied Intuition, which raised a $600M Series F round at a $15B valuation.

Robotics and cybersecurity follow closely, with AI firms in those sectors securing median deal sizes $10.7M and $6.4M larger than their non-AI peers.

Team pedigree is further amplifying the premium. Thinking Machines Lab — founded by former OpenAI CTO Mira Murati alongside veterans from OpenAI, Google, Meta, and Mistral AI — raised a record-breaking $2B seed round at a $10B valuation, making it the most valuable seed-stage startup ever. 

The deal reflects an increasingly common “go big or go home” investing mentality, as investors make outsized bets on high-credibility AI teams.

4. Regulatory shifts push big tech from M&A to minority investments

Big tech M&A — which includes M&A from Alphabet, Amazon, Apple, Microsoft, Meta, and Nvidia — is entering a sustained downturn. Annual deal activity is projected to hit just 12 transactions in 2025, a steady decline from 66 deals in 2014. 

US regulatory tightening caused M&A activity to collapse from 30+ deals in 2022 to just 8 deals in 2023 — the steepest single-year decline on record.

CBI customers: Track big tech M&A activity

Big tech companies are adapting by taking large minority stakes, allowing them to circumvent federal antitrust review while still gaining strategic influence and access to key technologies. For example, Meta invested $14.8B in Scale — the largest funding round of Q2’25 — for a 49% stake, as did Microsoft with its recent investments in OpenAI. 

In 2025 YTD, big tech is on pace for 14 corporate minority deals, an increase from levels before the regulatory shift.

Big tech’s shift reflects broader M&A weakness across the market. Global activity has fallen 34% from 3,103 deals in Q1’22 to 2,053 deals in Q2’25, driven by high interest rates that have made financing more expensive and economic uncertainty that has made companies more cautious about acquisitions.

However, acquisitions of AI companies is one area where M&A is increasing. Activity reached record levels in Q2’25 at 177 deals — over double the 5-year quarterly average of 84 deals. This surge reflects companies’ need to acquire AI capabilities quickly rather than build them internally, as AI becomes essential for staying competitive.

While falling interest rates will help smaller deals rebound and provide a modest tailwind to overall M&A activity, we do not expect deal volumes to approach peak years. Big tech and other large corporations will remain constrained by regulatory scrutiny.

We are likely entering a new era where strategic partnerships and minority investments replace traditional M&A as a growth mechanism for major corporations.

5. CVC deals hit a 7-year low as the tariff threat looms

Corporate venture capital dealmaking has reached its lowest point in over 7 years, as CVC-backed investment totaled just $17B across 742 deals, down 8% quarter-over-quarter and representing the weakest performance since Q1’18.

CVC activity has fallen dramatically from its Q1’22 peak due to broader market pressures, including high interest rates and economic uncertainty. Tariff concerns are likely adding further burden to an already weakened market.

Despite fewer deals, median CVC-backed deal sizes have reached their highest levels since 2021. This suggests that CVCs are concentrating capital on fewer, higher-conviction investments.

CVCs are also collaborating more frequently. Deals involving 3+ CVCs reached a record high of 32% in Q2’25, reflecting both strategic necessity and market conditions: larger funding rounds in capital-intensive sectors like AI and hard tech may require multiple corporate partners to provide sufficient capital. At the same time, competition for access to the hottest technologies drives CVCs to team up rather than risk being shut out.

Breakout sectors of 2025

Below, we analyze venture funding across tech sectors to identify where investor conviction and market momentum are strongest.

Stablecoin funding is on pace to shatter its previous record

Stablecoin startups are experiencing an explosive year-over-year funding surge as stablecoins achieve mainstream adoption. Funding is projected to reach $10.2B in 2025, representing more than 10x growth from 2024.

Growing regulatory frameworks worldwide — such as the pending passage of stablecoin legislation in the US with bipartisan support — provide needed certainty for institutional investment, setting the foundation for exponential growth.

Multiple startups are taking advantage of the momentum. While the largest funding rounds occurred during the first quarter — with $2B deals for Avalon Labs and Binance — notable rounds also occurred during Q2’25, including:

• Flowdesk: $100M for digital asset trading and liquidity services
• Conduit: $36M for its cross-border business transactions platform
• Niural: $31M for an AI-enabled stablecoin and fiat payroll platform

Major financial services companies are also increasingly involved. Mastercard, Visa, and established banks are now enabling stablecoin transactions and issuing their own digital currencies, bringing institutional credibility to the space. Meanwhile, stablecoin issuers Circle and Ripple applied for banking licenses on June 30 and July 2, respectively, demonstrating their intent to operate like mainstream financial institutions.

Stablecoins are evolving beyond simple stores of value into yield-bearing tools and liquidity products. Solutions like liquidity mining, lending services, and yield-bearing stablecoins are receiving substantial investor attention. Cross-border payments companies powered by stablecoins are also gaining traction as affordable and accessible USD alternatives in emerging markets.

As regulatory frameworks solidify and institutional adoption accelerates, stablecoin companies are positioned to capture significant market share in global payments and financial infrastructure markets.

Defense tech momentum continues

Within the first two quarters of 2025, defense tech funding has already reached a new annual record of $11.1B.

The funding breakout is driven by multiple forces, including geopolitical instability and technology advancements, notably in drones and other unmanned vehicles.

Concurrently, the US Department of Defense is pushing to diversify the defense ecosystem through public-private partnerships and startup support.

The defense investor landscape is also rapidly evolving, with the number of unique investors in the space expected to increase 34% in 2025 to 950 from 710 the year prior. Traditional defense funds like Shield Capital and In-Q-Tel are now joined by generalist VCs, bringing more capital to fund a new generation of startups.

We expect continued investor interest in defense tech, as NATO recently agreed to increase defense spending from 2% to 5% of GDP by 2035, adding over $400B annually in market expansion. The 1.5% earmarked for security infrastructure aligns with venture trends in AI, cybersecurity, robotics, and technologies developed for both military and civilian use cases.

Quantum tech reaches an all-time high, halfway through the year

Quantum tech is attracting significant investor interest, reaching record annual funding levels at $2.2B within the first two quarters of 2025 — an increase of 69% from 2024.

The surge follows major hardware breakthroughs from Google, IBM, and Microsoft, which may drive confidence in leading startups even though the technology still lacks practical applications that outperform classical systems. Industry leaders like Fujitsu and Quantinuum — a subsidiary of Honeywell — expect fault-tolerant quantum computers by 2030 at the earliest.

Massive investments are flowing towards various quantum applications in 2025 so far:

• PsiQuantum: $750M to build million-qubit photonic quantum computers by 2029
• QuEra Computing: $230M to accelerate fault-tolerant neutral-atom quantum systems
• Multiverse Computing: $215M to scale its quantum-inspired AI compression technology

Government support has also increased, with $1.8B in public funding announced globally in 2024. For example, Australia committed $620M to PsiQuantum, while DARPA committed up to $200M in joint funding to assess the feasibility of industrially useful quantum computers.

As quantum technologies move toward commercial viability, the combination of record private investment, substantial government backing, and technical progress positions the industry for significant growth once practical quantum advantage is achieved in commercial applications.

Corporate interest drives a surge in nuclear energy funding

Funding to nuclear energy companies is projected to reach an annual record by the end of 2025 at $5B. Massive energy requirements for AI data centers — with US data center power consumption projected to triple by 2030 — are driving corporate interest in clean baseload power.

Big tech companies are leading the charge, with investments since 2024 across both small modular reactors (SMRs) and fusion technologies:

• Amazon invested in X-energy with plans to develop over 5 GW of SMR projects by 2039; Amazon also backed Realta Fusion
• Google reached agreements with Kairos Power for up to 500 MW of nuclear power by 2030 and has also invested in Commonwealth Fusion Systems and TAE Technologies.
• Microsoft reached a deal with Constellation Energy to reopen the Three Mile Island nuclear plant, while committing to purchasing fusion electricity from Helion Energy by 2028

Corporate interest has also skyrocketed, with earnings call mentions hitting record levels as executives grapple with the major power requirements for AI infrastructure.

Current and previous presidential administrations have reduced regulatory red tape for nuclear development, streamlining approval processes. The bipartisan approach creates stable regulatory support for long-term investments and should accelerate sector growth in the coming years.

As AI adoption continues, nuclear provides the only scalable solution for clean baseload power that intermittent renewables cannot match for always-on AI computing infrastructure. The combination of massive corporate demand and supportive regulatory frameworks positions nuclear for explosive growth in the years ahead.

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RELATED RESOURCES FROM CB INSIGHTS:

• State of Venture Q1’25 Report
• The AI agent market map
• 7 tech M&A predictions for 2025
• State of AI Report: 6 trends shaping the landscape in 2025
• 15 tech trends to watch closely in 2025

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Military technology is entering its AI era.

Funding to AI companies targeting defense applications has reached $1.5B this year. At the current rate, this year will set a new record for the sector.

Public-company execs also have defense on the brain. 

Last quarter saw earnings call mentions of “defense” reach an all-time high, according to CB Insights’ Earnings Transcript Analytics.

Growing geopolitical tensions combined with AI advances are fueling the investment surge. 

Much of the activity centers on multidomain operations (MDO) technologies — integrating systems across land, sea, air, space, and cyber — where AI is accelerating mission planning, threat detection, and battlefield connectivity. 

Below, we look at:

1. Recent partnerships and the year’s biggest deals
2. Anduril’s UUV announcement
3. Top investors in 2025

1. Recent partnerships and the year’s biggest deals

Major defense contractors are forming partnerships with AI startups to pilot more autonomous capabilities. 

For instance, defense contractor L3Harris partnered with Shield AI in February to combine L3Harris’ electronic warfare capabilities with Shield AI’s autonomous flight tech. 

The next month, L3Harris invested in Shield AI’s $240M Series F alongside a16z, Booz Allen Hamilton, and others. 

That round is the 3rd-largest AI defense deal we’ve seen in 2025 so far, surpassed only by:

• Saronic’s $600M Series C. Saronic develops autonomous surface vessels for naval defense.
• Epirus’ $250M Series D. Epirus creates high-power microwave systems for counter-drone and electronic warfare applications.

Meanwhile, last week, SandboxAQ (an Alphabet spinout) raised a $150M extension to its $300M Series E from December. Its AQNav product is a real-time navigation system that combines AI and quantum sensing, with the aim of operating in areas where GPS is jammed or otherwise unavailable.

SandboxAQ is a leader in the quantum sensing market, alongside players like Q-Ctrl and Aosense — both of which partnered with Lockheed Martin last month on quantum-led navigation for GPS-denied environments. 

2. Anduril’s UUV announcement

AI defense leaders are also making gains in commercializing more advanced autonomous systems. 

This week, Anduril unveiled an unmanned underwater drone equipped with torpedo-like capabilities. Anduril was last valued at $14B in August, making it the most highly valued private AI defense firm.

We featured Anduril in several areas of our recent AI in defense tech market map. Customers can use the below links to see how Anduril stacks up against competitors in these markets:

• Loitering munition unmanned aerial vehicles (UAVs): Drones that loiter over an area for extended periods of time, providing intelligence before engaging targets with a precision strike
• Tactical unmanned underwater vehicles (UUVs): Autonomous or remotely operated submersibles that carry out a range of military and strategic tasks below the water’s surface

CBI customers can unlock the full map here.

3. Top investors in AI defense tech in 2025

8VC and a16z rank among the top investors in AI defense tech this year — but they’re outpaced by one peer who has already backed 4 AI defense tech companies in 2025.

CB Insights customers can see who it is using this platform search.

Related CB Insights research:

• The AI in defense tech market map
• State of Venture Q1’25 Report
• The quantum information market map: The companies working on quantum computing, post-quantum cryptography, and more
• Analyzing a16z’s AI investment strategy: How the VC is funding the AI global takeover

For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

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Prefer to listen in? Check out our discussion of the report here: 

New breakthroughs are altering the future direction of tech and its influence on the world at large.

While AI has captured headlines, it’s just one part of a broader technological surge. Startups and tech giants alike are making strides in fields as diverse as clean energy, space exploration, and human longevity.

Our Game Changers 2025 report highlights 9 emerging technologies that could transform how we live, work, and interact with our environment over the next 5-10 years and beyond. 

These include:

• Ultra-deep drilling: Advanced drilling techniques that can go far deeper to unlock superhot rock energy
• AI agent marketplaces: Enabling dynamic integration and collaboration of specialized agents across software platforms 
• Quantum-optimized portfolios: Using quantum computing to build higher-performing portfolios, faster
• Cellular & epigenetic reprogramming: Altering the gene expression of cells to extend the healthy human lifespan
• GPS-less navigation systems: Approaches that boost the resiliency and accuracy of positioning services critical to global infrastructure

Download the full report to explore all 9 technologies and the data behind them — including drivers, startups, and implications — in detail.

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Nvidia has used its experience developing graphics processing units (GPUs) — which were originally developed for applications like gaming but turned out to be rather good at AI tasks — to become a dominant force in AI infrastructure and applications. 

But a host of established companies and startups are investing heavily to capture a share of the growing AI computing market. This includes building new types of chips specifically for training and running AI models, evolving traditional processors like CPUs and GPUs to better support AI workloads, and exploring novel information processing technologies such as quantum and neuromorphic computing. 

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Humans will still play a crucial role — but instead of assembling parts or operating machinery, they will maintain robots and keep them running.

In these future factories, robots coordinate in unison, completing work automatically — without breaks, every hour of the day — to get products out the door. 

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Beyond relevance to government agencies, IQT’s investment activity has historically pointed to next-gen technologies that have the potential to be developed for use beyond the public sector.

IQT has participated in over 50 disclosed deals since the beginning of 2022, with many of its investments falling into areas categorized as “deep tech” — cutting-edge technologies rooted in scientific or engineering advances, such as biotech and quantum computing.

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While Nvidia initially developed its graphics processing units (GPUs) for gaming, these chips turned out to be ideal for powering AI tasks. Now, the company is focusing its efforts on providing the computing hardware — notably its A100 and H100 GPUs — and the software infrastructure required for developing generative AI applications.

Amid the generative AI rush, Nvidia has grown rapidly. In fact, it recently surpassed Microsoft and Apple to become the world’s most valuable company. To bolster its leadership position and keep ahead of AI computing competitors like AMD and Intel, Nvidia has forged relationships with companies across the AI landscape.

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The industry is built around encoding information in quantum entities called “qubits” — which have a probability of being either 1 or 0, as opposed to traditional bits that can only be one or the other — to open up new computational approaches and ways of handling data that are not possible on conventional devices.

For example, quantum computing could allow entirely new algorithms that are much more efficient at some key tasks — like complex optimization problems, sorting through large datasets, and running simulations. Though the tech is not yet mature, companies are already working to apply quantum computing to commercial applications like drug discovery, finance, materials discovery, and logistics. Investors are excited — startups in the space saw equity funding surge to $1.3B in 2023, a rare bright spot for venture last year. As quantum computers become more capable in the coming years, expect commercial interest to rise quickly.

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Funding to the space set a new record in 2023 — bucking the broader decrease in venture funding for the second year in a row.  

While still a nascent technology, startups are pursuing a broad range of potential use cases for quantum computing (which process information in a fundamentally different way to typical computers) across numerous industries — from training AI models more efficiently to simulating otherwise hard-to-model chemical reactions to quickly solving complex logistics problems, among many others.

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Startup valuations jumped for AI companies in 2023. Big tech is reaching new heights — as well as facing intensifying competition. Corporates are feeling the pressure to build their AI strategies and stay ahead of their peers.

At the same time, enterprises and investors have become more cautious spenders. Venture funding fell to a 6-year low in 2023. Many tech spaces will contend with consolidation in the year ahead, from digital therapeutics to cybersecurity.

Nevertheless, even with limited access to capital, startups continue to make commercial breakthroughs in areas like quantum computing, neurotech, and robotics.

We used the CB Insights technology intelligence platform to cut through the noise and identify 20 under-the-radar trends that will define tech in 2024. We analyzed signals like tech company financings, executive chatter in earnings transcripts, business relationships, customer perspectives, patents, and more.

Our 129-page report digs into trends across major industries including:

• AI
  • GPU shortage forces companies to be smarter
  • Multimodal AI will rise on corporates’ wish lists
  • Synthetic data bonanza
• Enterprise
  • DIY software development upends engineering orgs
  • Global employment & payroll market shakes out
  • Quantum computing advances hint at faster commercialization
• Cybersecurity
  • Cyber chaos drives security consolidation
  • AI vs. AI dogfights redefine data security
• Healthcare & life sciences
  • The great AI drug race heats up
  • Digital therapeutics (DTx) & wellness consolidates
  • The brain becomes a fierce tech battleground
• Financial services & insurance
  • Banks get AI FOMO
  • Blockchain’s uphill finserv battle
  • Extreme weather is an opportunity for insurtech
• Retail & consumer
  • AI sales agents flood the e-commerce landscape
  • Retailers tackle shrink with AI loss prevention
  • AI sends a shockwave through gaming
• Industrials
  • Humanoid robots come for manufacturing
• Venture
  • Corporate venture refocuses on strategic fit
  • Unicorns need a new playbook to survive

Download the full report to see all 20 trends and identify disruptive tech markets, how incumbents are preparing, and the startups vying to change industries.

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At the heart of its growth strategy is the integration of AI. In 2017, the company founded the Bosch Center for Artificial Intelligence — a global team dedicated to advanced AI research — while investing over $100M+ into a new AI campus. The company’s 2025 goal is to incorporate AI in all of its products or develop them using AI.

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Research & development (R&D) productivity has steadily declined over the past century, which means businesses must spend more on R&D to keep technological advancement moving forward. The manufacturing sector alone accounts for over half of total R&D investment in the US, according to the National Science Foundation. 

However, an emerging set of technologies — ranging from augmented reality design tools to quantum computing simulations — offers manufacturers an opportunity to reduce costs and drive efficiencies in product design and development.

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Although the loss was in part driven by an expensive, ongoing strategic transition, Intel highlighted a number of factors — such as decreasing PC demand and declining data center markets — that negatively impacted results and reflect headwinds in the semiconductor industry broadly.

Startups have been affected by the current downturn, with revenues and venture funding experiencing recent declines. However, there are several areas proving to be resilient to this change, including chips for AI, automotive, and quantum computing.

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This achievement is partly attributed to its pioneering work in accelerated computing, which uses specialty hardware to complete demanding software tasks much faster than previously possible.

Initially, this effort was primarily focused on gaming — but NVIDIA’s development of parallel processing in 2006 paved the way for new capabilities in scientific and research applications. This breakthrough allowed multiple computations at a given time instead of sequentially, resulting in much faster processing speeds.

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By using quantum phenomena to process information in a new way, churning through calculations for certain tasks — such as simulations, data analysis, and optimization — could go from taking many lifetimes to finishing up faster than it would take to make a cup of tea. This dramatic acceleration would open the door to a whole new set of computational tools for businesses.

While quantum computing is still nascent, its implications are far-reaching and will impact a host of industries, including banking, healthcare, and cybersecurity.

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But as more companies vie for backing and early customers, enterprises and investors face the challenge of cutting through the noise to identify the most promising startups.

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The search giant is building advanced quantum computing hardware, has a strong focus on developing quantum AI, and is putting significant energy into achieving scientific breakthroughs around quantum. Alphabet (Google’s parent company) also has a secretive non-Google team called Sandbox working on quantum tech. Expect Google to look to gain an edge by integrating quantum-powered AI capabilities throughout its product ecosystem.

We dig into all of these themes, and more, below.

Read more about big tech’s quantum activity in the full Big Tech In Quantum Report.

Google is building cutting-edge quantum technology

Google targets 1M qubits by the end of the decade

Google builds its own quantum computers, and its machines are currently among the most powerful in the world — though not yet capable enough for useful commercial applications.

Google is planning to up the number of qubits (what quantum computers use to calculate things — the more the better) to 1M by the end of the decade. The company believes this will be enough to run an error-corrected, commercially relevant quantum computer.

Google just opened a quantum computing campus

Google has built a quantum AI campus and data center in Santa Barbara, California to house its main quantum computing efforts.

This indicates that it is doubling down on its quantum computing bets and is expecting the tech to become a more significant part of its business.

Source: Google

Alphabet has a secret, non-Google quantum effort

Alphabet has a software-focused quantum team called Sandbox that is dedicated to applying quantum technology to near-term enterprise use cases. Sandbox operates mostly in stealth mode; however, recent job postings and past comments from its leadership indicate that its work includes:

• Quantum sensors — There are hints that Sandbox is working on a hypersensitive magnetism-based diagnostic imaging platform, possibly a magnetoencephalography (MEG) system for reading brain activity, that combines quantum-based sensitivity gains (tens of thousands of times more sensitive than typical approaches) with quantum machine learning to disentangle a signal from background noise to boost sensitivity. This could allow for more precise scans or for cheaper, more flexible deployments of magnetic-based imaging devices for use beyond hospital settings, as well as improved access in lower-income countries.
• Post-quantum cryptography (PQC) — Quantum computers threaten much of the encryption used on the internet. Post-quantum cryptography will defend against this. Expect Sandbox’s work to be focused on helping enterprises transition to PQC and making Alphabet’s sprawling online services quantum-safe. (Find out more about post-quantum cryptography in our explainer.)
• Distributed computing — This tech allows computers to coordinate processing power and work together on problems. Sandbox’s work here may focus on integrating near-term quantum computers into distributed computing networks to boost overall capabilities. Another approach would be to use quantum optimization algorithms to help manage distributed networks more efficiently.

Google has made scientific breakthroughs

Google establishes itself as a quantum science leader

Google partners liberally on quantum initiatives

Google has partnered with several quantum computing startups — including QSimulate, IonQ, AQT, and Pasqal — on quantum computing projects. This helps Google tap into additional industry expertise while more tightly weaving its quantum computing platforms into the broader ecosystem.

The tech giant is also working with numerous university teams and some corporations, including Nvidia and Boehringer Ingelheim.

Google’s quantum advances keep it in the news

Google could benefit from a quantum AI ripple effect through its businesses

Google thinks that quantum AI is a killer early app

Google’s main quantum efforts are branded under Google Quantum AI and the company sees artificial intelligence as a key application of quantum computers — even in the near term with only moderately powerful machines.

Google has also developed an open-source platform for building quantum machine learning models, TensorFlow Quantum.

Source: Google

AI is key to Alphabet’s long-term business goals

Alphabet is investing heavily in all sorts of AI tools to integrate into its businesses. Though quantum machine learning is only one aspect of this broader strategy, the company is indicating through its big bets in the space that it is bullish on the tech. If it succeeds, then Alphabet could use quantum computing to eventually boost AI initiatives across its entire business.

“As we are thinking about AI, it all starts with foundational R&D we do. I think we are one of the largest R&D investors in AI in the world. And so thinking ahead and doing that and we are doing it across all the foundational areas and we are taking many diverse approaches.” — Sundar Pichai, Alphabet CEO, Q1’21 earnings call

Alphabet’s businesses are set to go quantum

Many of Alphabet’s businesses make use of AI in some capacity. These areas could be given a significant boost by advances in quantum AI, including business lines like:

• Search and ads — Quantum computing will allow for better ways to parse through big datasets quickly. Advances in natural language processing (NLP) that stem from quantum machine learning could help deliver more relevant and targeted search results and ads.
• Waymo — Quantum machine learning could help AI make faster decisions based on less data. Applying this to self-driving car tech could help autonomous vehicles better adapt to dynamic situations on the fly.
• Google Assistant — Just as quantum NLP could help Google better understand websites, it could also help its voice assistant better interpret requests. The company may be hoping to gain a quantum edge over rival voice assistants.
• Google Cloud — As well as offering cloud-based quantum computing services to enterprises, Google could use quantum algorithms to better manage tasks like cloud data storage.
• DeepMind — DeepMind has built a reputation for pushing AI capabilities to the edge, like with its protein folding prediction tool for drug discovery. Quantum machine learning would amplify many of DeepMind’s tools and may eventually help defend against competitors looking to catch up with it.

Looking ahead

To find out how Microsoft, Amazon, IBM, and Intel are competing with Google, check out the full Big Tech In Quantum Report.

The post Google In Quantum: How The Tech Giant Is Competing For The Next Era Of Computing appeared first on CB Insights Research.

Funding to quantum tech startups soared to record levels in 2021. Media interest in the space has continued to climb. New milestones and scientific breakthroughs are being announced at a quickening pace.

Against this backdrop, big tech companies Google, Microsoft, Amazon, IBM, and Intel are investing heavily in building their own quantum computers and developing applications around enterprise use cases.

With enormous prizes on the horizon, none of these big tech companies want to be left behind.

Download the report to find out:

• How big tech companies are looking to gain from quantum advances and their strategies for commercializing quantum computing
• The different approaches they are using to develop their own quantum computers
• How big tech giants are using partnerships to build out their quantum capabilities and stake out market positions
• Which strengths and capabilities differentiate each big tech company in quantum

REPORT HIGHLIGHTS:

• Big tech’s quantum activity is ramping up quickly. Google, Microsoft, Amazon, IBM, and Intel are all developing their own quantum computing hardware. Big tech companies have already been behind several breakthroughs in the space.
• Cloud is an early area of quantum competition for big tech. Google, Microsoft, Amazon, and IBM have all launched quantum computing services on their cloud platforms. Numerous startups have partnered with big tech companies to offer remote access to a broad range of quantum computers.
• Big tech is poised to forge ahead with quantum advances. Google, Microsoft, Amazon, IBM, and Intel all have ambitious quantum roadmaps. Expect rising qubit counts and more frequent demonstrations of commercial applications.
• Watch for quantum computing to become a hot geopolitical issue, especially for US-China relations. Expect quantum-forward big tech companies, including China-based Baidu and Alibaba, to be drawn deeper into political debates. In the US, government efforts to rein in big tech could be countered by officials nervous about keeping up with countries racing ahead with quantum technology.
  

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Quantum computers process information in a fundamentally different way than today’s conventional computers. This allows them to conduct new types of calculations that otherwise wouldn’t be possible. In theory, quantum-forward banks could build trading strategies that offer better returns, quickly parse through different portfolio combinations to find the best mix of investments, and supercharge risk analysis for tasks like issuing credit.

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Quantum computers process information in a fundamentally different way than their classical counterparts. Eventually, they will be able to quickly crack many of today’s public-key encryption methods — a form of encryption that underpins the security of emails, payments, digital certificates for proving the authenticity of websites, and more.

The stakes are high. Any organization relying on current methods for public-key encryption — including banks, shops, and hospitals — would be vulnerable to being hacked, making even the worst data breaches of recent years pale in comparison.

Though this “quantum time bomb” will likely not go off for a while, the risk is quickly becoming a high priority given the accelerating pace of quantum computing advances. Transitioning to new encryption protocols could take years — or even decades — to complete.

However, new public-key encryption techniques that can defend against this quantum threat are already emerging. Known collectively as “post-quantum cryptography (PQC),” these techniques employ encryption algorithms that even a quantum computer couldn’t easily crack, and are sometimes described as being “quantum-resistant” or “quantum-safe.” Interest in the PQC space is rising quickly, with media mentions skyrocketing in 2021.

The stage is set for a race between the adoption of post-quantum cryptography and the development of powerful quantum computers. Post-quantum cryptography has a head start, but quantum computing advances are accelerating.

Funding is pouring into quantum computing companies like PsiQuantum, Rigetti, Cold Quanta, and many others hoping to disrupt major industries. Google, Microsoft, Amazon, IBM, Honeywell, and other big corporations have placed enormous bets in the space.

All it takes is for one quantum computing approach to succeed for much of the internet to no longer be considered secure. In this report, we break down how post-quantum cryptography works, who the key players are, what companies should consider for adopting PQC, and more.

Table of contents

• What is post-quantum cryptography?
• Who are the post-quantum cryptography players?
• What should a company consider for adopting post-quantum cryptography?
• What’s ahead for post-quantum cryptography?

Learn how quantum computers work, the industry landscape, and the tech’s applications beyond cybersecurity in this deep dive report. CB Insights clients can track quantum computing companies using our Quantum Tech Expert Collection.

What is post-quantum cryptography?

Post-quantum cryptography typically refers to public-key cryptography methods that are designed to be resistant to quantum computer-based attacks.

How does public-key cryptography work?

Public-key cryptography, also known as “asymmetric cryptography,” lets multiple parties communicate securely over an open network without having already agreed on an “encryption key” — a code that can be used to scramble information and make it meaningless to observers without the right key.

Public-key encryption allows someone to send out a public key that can encrypt information but cannot decode it. Anyone can see the public key and use it to encode messages, but only the person who has the matching private key can decrypt it. The public key functions like an open padlock — anyone who finds it can close it to secure something, but only the person who has the padlock’s key can open it again.

This means that different parties can pass messages over the internet that only the recipient can read. Today, quantum-vulnerable methods for public-key cryptography — such as RSA encryption — are used widely and underpin the security of lots of online activity, from messages to payments to logging into a website.

Why do quantum computers threaten today’s public-key cryptography?

Public keys and private keys are mathematically linked. Today’s methods for public-key cryptography rely on mathematical problems that conventional computers find extremely difficult, such as finding the prime factors of a very large number.

But quantum computers process information in a way that allows them to do some types of calculations that classical computers can’t.

This includes Shor’s algorithm, which provides a highly efficient way to tackle the very mathematical challenges currently keeping much of our public-key-based online communications private. If Shor’s algorithm was being run by a powerful quantum computer, then most of today’s public-key cryptography approaches wouldn’t hold up.

This is where post-quantum cryptography comes in.

How does post-quantum cryptography defend against quantum computers?

PQC links private keys to public keys without using problems that quantum computers can easily solve. In other words, it aims to deliver the benefits of today’s public-key encryption without the vulnerability to quantum hacking.

Approaches to PQC include building encryption around mathematical “structures” called lattices, using systems purely based upon code, solving complicated problems involving multiple variables, and much more.

Who are the post-quantum cryptography players?

Post-quantum cryptography is attracting attention from organizations including governments and affiliated agencies, corporations, and startups.

The National Institute of Standards and Technology (NIST), a US-based standard-setting body, is a central player in the space. It’s currently evaluating leading post-quantum cryptography candidates and is due to announce new standards for public-key encryption within the next year or so.

But activity in the sector is picking up even as companies wait for NIST to complete its process:

• Major tech players including Microsoft and IBM are developing their own candidates for post-quantum cryptography algorithms.
• Amazon’s AWS cloud platform has begun to offer support for some PQC protocols.
• Intel is working on ways to bring PQC to low-powered IoT devices.

With a lot of money riding on the security of their transactions, big financial companies are also making early moves. For example, Mastercard recently launched a new wireless payments protocol that it claims is quantum-safe. Meanwhile, its rival VISA has published multiple papers exploring how PQC could affect payments. JPMorgan is reportedly already combing through its systems to identify which data to prioritize for a quantum-safe revamp.

Meanwhile, a growing number of startups are looking to gain an early-mover advantage and position themselves for a coming surge in demand. ISARA, PQShield, and Post-Quantum are among the most well-funded companies in the space, with all 3 aiming to help enterprises and governments transition to post-quantum cryptography systems.

Other startups are working on niche quantum-resistant applications, such as more secure blockchains (Cellframe), protecting IoT systems (AgilePQ), and encrypted telehealth platforms (Cyph).

CB Insights clients can check out the full quantum tech market map here and can see many more post-quantum cryptography companies in our Quantum Tech Expert Collection. 

What should a company consider for adopting post-quantum cryptography?

Pretty much every company will eventually move to some form of post-quantum cryptography, but when and how will be key considerations.

What cybersecurity threat do quantum computers pose to companies?

Most of what a company does online could be impacted by the onset of powerful quantum computers. This is because public-key cryptography plays a role in all sorts of things, including:

• Sending messages online
• Facilitating online payments
• Logging into websites
• Blockchain applications
• Accessing data stored online
• Securing IoT devices

This means that a company that was not protected against a quantum computer-backed hack would not be able to meaningfully assure customers that its systems were secure once a powerful quantum computer emerged.

When will companies need to adopt post-quantum cryptography?

A number of cybersecurity players, including researchers working for NIST and the UK’s National Cyber Security Centre (NCSC), are recommending that enterprises already begin laying the groundwork for migrating to post-quantum cryptography and then move quickly to implement new encryption approaches when PQC standards are announced.

But some in the space also caution against actually committing to a particular PQC approach until standards have been set within the coming year or so.

The quantum threat won’t materialize overnight, but transitioning to post-quantum cryptography will take a long time

Though it is widely accepted that quantum computers will eventually render a lot of today’s public-key encryption obsolete, the actual timeline is impossible to predict. Most estimates fall within the range of 10-20 years, but the threshold could be passed much earlier if quantum computer producers make an unforeseen breakthrough.

For instance, PsiQuantum, the most well-funded quantum computing startup in the world, claims that it will have a 1M qubit quantum computer within just a few years. (Qubits are what quantum computers use to conduct calculations. Read about how they work in this explainer.) If achieved, this would signal that the tech is evolving much faster than many thought possible.

Quantum computer maker PsiQuantum raised a $450M mega-round at a $3B+ valuation in July. 

In any event, transitioning to post-quantum cryptography is expected to take a decade or more, driving a sense of urgency to upgrade systems as soon as possible so that companies aren’t caught off guard when capable quantum computers emerge.

Data harvested now can be decrypted later

Data encrypted with quantum-vulnerable algorithms can be intercepted now and stored for a time when powerful quantum computers exist. This is a key concern for governments wanting to guard secrets, but companies dealing with sensitive information — such as key IP or some types of personal information — may also need to develop a strategy to counter this drawn-out hack.

Implementing PQC for high-priority data will solve this issue going forward, but nothing can be done for information that has already been squirreled away.

Standards haven’t arrived yet, but preparations can already begin

Many companies are waiting until NIST announces its post-quantum cryptography standards before making the leap. This approach reduces the likelihood of running into interoperability issues and will help ensure that the PQC approach being deployed actually works as intended.

However, enterprises can still make moves to start preparing for PQC. This includes:

• figuring out how they are currently using public-key cryptography
• understanding the requirements and constraints of their systems (issues like data latency needs, hardware specs, and legal compliance could all influence a transition to PQC)
• identifying what data is especially sensitive

What are the barriers to the adoption of post-quantum cryptography?

Public-key cryptography is used everywhere; updating it will be challenging

Transitioning to post-quantum cryptography will be difficult. Public-key cryptography is used in lots of different ways for a broad range of purposes, from passwords to digital signatures for websites to facilitating other types of encryption.

Successfully updating all of these instances is unlikely to be as simple as a software update. Depending on the circumstance, it may require new hardware, installing infrastructure, redrafting security protocols, or even renegotiating contracts with external partners.

Given this complexity, a major cybersecurity risk going forward is that some companies may be tempted to not bother upgrading their systems.

Post-quantum cryptography approaches vary widely in their advantages and constraints; expect different standards for different applications

In general, post-quantum cryptography will be more taxing on computers than what is currently used, but some will need more power than others and different approaches will offer varying risk profiles.

Given the broad set of tasks that public-key encryption is used for, it’s possible that NIST will recommend different PQC standards depending on the use case. For example, one approach may be recommended for low-powered IoT devices not carrying highly sensitive data, while another may be recommended for tasks like facilitating online data storage.

How does quantum key distribution relate to post-quantum cryptography?

Another encryption technology to keep an eye on is “quantum key distribution” (QKD), sometimes referred to as “quantum cryptography.” This approach taps into quantum phenomena to transmit an encryption key in such a way that its quantum state measurably changes when the message is read. This means that even a quantum computer-equipped hacker would not be able to intercept the encryption key without giving themselves away.

In theory, this provides an extremely secure way to transmit encryption keys, but it can be challenging to implement properly in practice and it can’t do everything that public-key cryptography approaches can (such as authenticating who you’re actually speaking with).

National security-minded agencies like the NSA have also warned that QKD introduces other forms of risk. For example, since QKD systems are designed to fail if someone intercepts the transmission, it actually provides a way for an adversary to cause problems by intentionally interrupting communications.

The technology also currently requires specialized equipment and is limited to relatively short distances (though new QKD distance records are regularly being set).

Despite these challenges, QKD is gaining traction and will become more common in the future. Toshiba, for example, is expecting to generate $3B in revenue from QKD services by the end of the decade. A growing number of quantum communication startups — including SpeQtral, Quantum Xchange, and KETS — are also working on QKD systems.

However, the tech will likely have to be deployed alongside other cybersecurity measures, including post-quantum cryptography, to be effective.

Given the above, companies should not think of QKD as an alternative to PQC but as a complementary cybersecurity tool that could be useful for specific applications related to some high-value data.

CB Insights clients can check out our quantum tech market map here and can see many more quantum key distribution companies in our Quantum Tech Expert Collection. 

What’s ahead for post-quantum cryptography?

Post-quantum cryptography is already gaining momentum with businesses, but interest will surge when NIST announces its PQC standards.

More vendors are also entering the space. Early-stage startups like QuSecure, Code-X, and QANplatform have raised funding this year to build out quantum-resistant tech. Expect more players to spring up as demand for post-quantum cryptography products grows over the coming months and years.

Quantum computers are advancing rapidly and companies should continue to monitor the space. Funding is pouring into startups, quantum computing-related patents are on the rise, and new developments are regularly being announced. Tech giants like Google, Microsoft, and Amazon are betting big on the tech. Though the trajectory of the emerging quantum technology space is uncertain, the likelihood of a powerful quantum computer emerging in the not-too-distant future feels higher than ever.

Companies that balance the urgency of migrating to PQC alongside steady, deliberate decision-making stand to be most well-positioned. Moving too quickly presents pitfalls, especially around interoperability or being hamstrung by hard-to-fix constraints, but waiting until a powerful quantum computer is about to be launched would be far too late.

Cybersecurity risks aside, powerful quantum computers have disruptive applications across a wide range of industries, including finance, healthcare, logistics, and more — find out more in this report. 

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Big tech companies are leveraging their expertise in software, data, and AI to capitalize on rising opportunities in the space, from research and discovery to clinical development to patient monitoring.

Amazon, for example, is working to build out a digital pharmacy following its 2018 acquisition of PillPack. Meanwhile, Microsoft is using its AI capabilities to make the drug discovery process more efficient.

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The emerging technology has the potential to reshape countless sectors, but some will have to adapt more quickly than others.

Below, we look at 9 spaces where quantum computing is already making waves.

1. Healthcare

Quantum computers could impact healthcare in a number of ways.

For example, Google recently announced that it had used a quantum computer to simulate a chemical reaction, a milestone for the nascent technology. Though the specific interaction was relatively simple — current classical computers can model it too — future quantum computers should be able to simulate complex molecular interactions much more accurately than classical computers. Within healthcare, this could help speed up drug discovery efforts by making it easier to predict the effects of drug candidates.

Another area where drug discovery could see a boost from quantum computing is protein folding. Startup ProteinQure — which was featured by CB Insights in the 2020 cohorts for the AI 100 and Digital Health 150 — is already tapping into current quantum computers to help predict how proteins will fold in the body. This is a notoriously difficult task for conventional computers. But using quantum computing to address the issue could ultimately make designing powerful protein-based medicines easier.

Source: ProteinQure

Eventually, quantum computing could also lead to better approaches to personalized medicine by allowing faster genomic analysis to inform tailored treatment plans specific to every patient.

Genome sequencing creates lots of data, meaning that analyzing a person’s DNA requires a lot of computational power. Companies are already rapidly reducing the cost and resources needed to sequence the human genome; but a powerful quantum computer could sift through this data much more quickly, making genome sequencing more efficient and easier to scale.

A number of pharma giants have shown interest in quantum computing. Merck’s venture arm, for instance, participated in Zapata’s $38M Series B round in September 2020. Meanwhile, Biogen partnered with quantum computing software startup 1QBit and Accenture to build a platform for comparing molecules to help speed up the early stages of drug discovery.

CB Insights clients can check out this report for more on how quantum technologies are reshaping healthcare.

2. Finance

Financial analysts often rely on computational models that build in probabilities and assumptions about the way markets and portfolios will perform. Quantum computers could help improve these by parsing through data more quickly, running better forecasting models, and more accurately weighing conflicting possibilities. They could also help solve complex optimization problems related to tasks like portfolio risk optimization and fraud detection.

Another area of finance quantum computers could change are Monte Carlo simulations — a probability simulation used to understand the impact of risk and uncertainty in financial forecasting models. IBM published research last year on a method that used quantum algorithms to outcompete conventional Monte Carlo simulations for assessing financial risk.

Source: IBM

A number of financial institutions including RBS, the Commonwealth Bank of Australia, Goldman Sachs, Citigroup, and more have invested in quantum computing startups.

Some are already starting to see promising results. John Stewart, RBS’s head of global innovation scouting and research told The Times newspaper that the bank was able to reduce the time taken to assess how much money needed to be offset for bad loans from weeks to “seconds” by using quantum algorithms developed by 1QBit.

3. Cybersecurity

Cybersecurity could be upended by quantum computing.

Powerful quantum computers threaten to break cryptography techniques like RSA encryption that are commonly used today to keep sensitive data and electronic communications secure.

This prospect emerges from Shor’s Algorithm, a quantum algorithm that was theorized in the 1990s. This technique describes how a suitably powerful quantum computer — which some expect could emerge around 2030 — could very quickly find the prime factors of large numbers, a task that classical computers find extremely difficult. RSA encryption relies on this very challenge to protect data being shuttled around online.

But companies are emerging to counter this threat by developing new encryption methods, collectively known as “post-quantum cryptography.” These methods are designed to be more resilient to quantum computers — often by creating a problem that even a powerful quantum computer wouldn’t be expected to have many advantages in trying to solve. Companies in the space include Isara and Post Quantum, among many more. The US National Institute of Standards and Technology (NIST) is also backing the approach and is planning to recommend a post-quantum cryptography standard by 2022.

Source: Post Quantum

Another nascent quantum information technology called quantum key distribution (QKD) could also offer some respite from quantum computers’ code-breaking abilities. QKD works by transferring encryption keys using entangled qubits. Since quantum systems are altered when measured, it’s possible to check if an eavesdropper has intercepted a QKD transmission. Done right, this means that even quantum computer-equipped hackers would have a hard time stealing information.

Though QKD currently faces practical challenges like the distance over which it is effective (most of today’s QKD networks are pretty small), many are expecting it to soon become a big industry. Toshiba, for instance, said in October 2020 that it expects to generate $3B in revenue from QKD applications by the end of the decade.

CB Insights clients can see private companies working on post-quantum cryptography and QKD in this market map.

4. Blockchain and cryptocurrencies

Quantum computing’s threat to encryption extends to blockchain tech and cryptocurrencies — including Bitcoin and Ethereum — which rely upon quantum-susceptible encryption protocols to complete transactions.

Though specific quantum threats to blockchain-based projects vary, the potential fallout in worst-case scenarios could be severe.

For example, about 25% of bitcoins (currently worth hundreds of billions of dollars) are stored in such a way that they could be easily stolen by a quantum computer-equipped thief, according to an analysis from Deloitte. Another fear is that quantum computers could eventually become powerful enough to decrypt and interfere with transactions before they’re verified by other participants on the network, undermining the integrity of the decentralized system.

And that’s just Bitcoin. Blockchain tech is being used more and more for applications within asset trading, supply chains, identity management, and much more.

Rattled by the profound risks posed by quantum computers, a number of players are moving to make blockchain tech safer. Established networks like Bitcoin and Etherum are experimenting with quantum-resistant approaches for future iterations, a new blockchain protocol called the Quantum Resistant Ledger has been set up that’s specifically designed to counter quantum computers, and startups including QuSecure and Qaisec say that they’re working on quantum-resistant blockchain tech for enterprises.

Quantum-resistant blockchains may not fully emerge until post-quantum cryptography standards are more firmly established in the coming years. In the meantime, those running blockchain projects will likely be keeping a nervous eye on quantum computing advancements.

Check out our explainer for more on how blockchain tech works.

5. Artificial intelligence

Quantum computers’ abilities to parse through massive data sets, simulate complex models, and quickly solve optimization problems have drawn attention for applications within artificial intelligence.

Google, for instance, says that it’s developing machine learning tools that combine classical computing with quantum computing, stating that it expects these tools to even work with near-term quantum computers.

Similarly, quantum software startup Zapata recently stated that it sees quantum machine learning as one of the most promising commercial applications for quantum computers in the short term.

Though quantum machine learning may soon offer some commercial advantages across a broad range of areas — including autonomous vehicles and predicting the weather — future quantum computers could take AI even further.

AI that taps into quantum computing could advance tools like computer vision, pattern recognition, voice recognition, machine translation, and more.

Eventually, quantum computing may even help create AI systems that act in a more human-like way. For example, enabling robots to make optimized decisions in real time and more quickly adapt to changing circumstances or new situations.

Take a look at this report for other emerging AI trends.

6. Logistics

Quantum computers are good at optimization. In theory, a complex optimization problem that would take a supercomputer thousands of years to solve could be handled by a quantum computer in just a matter of minutes.

Given the extreme complexities and variables involved in international shipping routes and orchestrating supply chains, quantum computing could be well-placed to help tackle daunting logistics challenges.

DHL is already eyeing quantum computers to help it more efficiently pack parcels and optimize global delivery routes. The company is hoping to increase the speed of its service while also making it easier to adapt to changes — such as canceled orders or rescheduled deliveries.

Others want to improve traffic flows using quantum computers, a capability that could help delivery vehicles make more stops in less time.

Source: Volkswagen

For example, Volkswagen, in partnership with D-Wave Systems, ran a pilot last year to optimize bus routes in Lisbon, Portugal. The company said that each of the participating buses was assigned an individual route that was updated in real time based on changing traffic conditions. Volkswagen states that it intends to commercialize the tech in the future.

7. Manufacturing and industrial design

Quantum computing is also drawing interest from big players thinking about manufacturing and industrial design.

For example, Airbus — a global aerospace corporation — established a quantum computing unit in 2015 and has also invested in quantum software startup QC Ware and quantum computer maker IonQ.

One area the company is looking at is quantum annealing for digital modeling and materials sciences. For instance, a decent quantum computer could quickly filter through countless variables to help determine the most efficient wing design for an airplane.

Other companies, including Daimler and Samsung, are already using quantum computers to help research new materials for building better batteries.

IBM has also identified manufacturing as a target market for its quantum computers, with the company highlighting areas like materials science, advanced analytics for control processes, and risk modeling as key applications for the space.

A selection of IBM’s envisioned manufacturing applications for quantum computing. Source: IBM

Though quantum computing will likely be implemented in manufacturing only gradually as more powerful machines emerge over the coming years, some companies — including machine learning startup Solid State AI — are already offering quantum-supported services for the industry.

8. Agriculture

Quantum computers could boost agriculture by helping to produce fertilizers more efficiently.

Nearly all of the fertilizers used in agriculture around the world rely on ammonia. The ability to produce ammonia (or a substitute) more efficiently would mean cheaper and less energy-intensive fertilizers. In turn, easier access to better fertilizers could help feed the planet’s growing population.

Ammonia is in high demand and is estimated to be a $77B global market by 2025, according to CB Insights’ Industry Analyst Consensus.

Little recent progress has been made on improving the process to create or replace ammonia because the number of possible catalyst combinations that could help us do so is extremely large — meaning that we essentially still rely on an energy-intensive technique from the 1900s known as the Haber-Bosch Process.

Using today’s supercomputers to identify the best catalytic combinations to make ammonia would take centuries to solve.

However, a powerful quantum computer could be used to much more efficiently analyze different catalyst combinations — another application of simulating chemical reactions — and help find a better way to create ammonia.

Moreover, we know that bacteria in the roots of plants make ammonia every day with a very low energy cost using a molecule called nitrogenase. This molecule is beyond the abilities of our best supercomputers to simulate, and hence better understand, but it could be within the reach of a future quantum computer.

9. National security

Governments around the world are investing heavily in quantum computing research initiatives, partly in an attempt to bolster national security.

Defense applications for quantum computers could include, among many others, code breaking for spying, running battlefield simulations, and designing better materials for military vehicles.

Last year, the US government announced an almost $625M investment in quantum technology research institutes run by the Department of Energy — companies including Microsoft, IBM, and Lockheed Martin also contributed a combined $340M to the initiative.

The US is investing more in quantum information science (QIS) research, including quantum computing. Source: The US National Quantum Coordination Office

Similarly, China’s government has poured billions of dollars into numerous quantum technology projects and a team based in the country recently claimed to have achieved a quantum computing breakthrough.

Though it is uncertain when quantum computing may play an active role in national security, it is beyond doubt that no country will want to fall behind the capabilities of its rivals. A new “arms race” has already begun.

For more on what quantum computers are, the investment landscape, and how the tech is being applied across industries, check out this report.

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Below, we look at what makes quantum computing different from today’s commonplace “classical” computing.

Some key differences between quantum computers and classical computers include:

• Quantum computers process information in a fundamentally different way to classical computers. Instead of relying on transistors — which can only represent either the “1” or the “0” of binary information at a single time — quantum computers use qubits, which can represent both 0 and 1 simultaneously. Read our quantum computing explainer for more on how this works.
• A quantum computer’s power grows exponentially in relation to the number of qubits linked together. This differs from a conventional computer, which sees its power increase in direct proportion to the number of transistors. This is one reason why quantum computers could eventually handle some types of calculations much better than classical computers.
• Though quantum computers could drastically outperform classical computers at some tasks — such as optimizing delivery routes or simulating a chemical reaction — they are difficult to build and there are lots of types of calculation where they aren’t expected to offer many advantages. As such, most everyday processing will likely be better handled by conventional computers even when powerful quantum computers begin to emerge.

For more on what quantum computers are, the investment landscape, and how they’re being applied across industries, check out this report.

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