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Monday, March 24, 2025

USA Presidential elections have a real impact on stock markets. So, How can one position oneself in the first year?

If we use the election cycle as a guide, especially for U.S. presidential elections, there are some historical patterns investors often pay attention to:

Post-election years (like 2025) often bring policy shifts (stimulus, deregulation, defense spending, etc.) that affect certain sectors.
The first year of a presidency often includes new government programs, spending packages, and regulatory changes—this can mean big moves for companies exposed to government contracts or regulation.

So, if we go by history and themes that often play well in post-election years, here are a few sectors and example companies to watch for potential gains in 2025:

⚙️ 1. Defense & Aerospace

New administrations (regardless of party) often increase defense budgets or reallocate them. Global tensions also drive this.

Lockheed Martin (LMT)
Northrop Grumman (NOC)
Palantir Technologies (PLTR) – also benefits from defense + AI + government contracting.

🏗️ 2. Infrastructure & Clean Energy

If a new or returning president pushes for infrastructure investment or green energy, watch for this boost.

Caterpillar (CAT) – infrastructure and construction machinery.
NextEra Energy (NEE) – strong in renewables.
Quanta Services (PWR) – electric grid, renewables infrastructure.
Tesla (TSLA) – if EV incentives ramp up again.

🏥 3. Healthcare & Biotech

Healthcare reform efforts and FDA funding shifts can heavily impact drug and medtech companies.

UnitedHealth Group (UNH) – strong during regulatory changes.
Eli Lilly (LLY) and Novo Nordisk (NVO) – if focus returns to obesity and diabetes solutions.
10X Genomics (TXG), Twist Bioscience (TWST) – if genomics and biotech innovation get funding support.

🧠 4. Artificial Intelligence & Cybersecurity

Governments are investing in AI infrastructure and cybersecurity regardless of party lines.

NVIDIA (NVDA) – chips powering AI.
SentinelOne (S) or CrowdStrike (CRWD) – cyber defense.
C3.ai (AI) – close to government contracts + enterprise AI.

💻 5. Semiconductors & Reshoring

Both parties push for U.S. manufacturing and chip independence.

Intel (INTC) – heavy government backing for fabs.
AMD (AMD) and Broadcom (AVGO) – tied to infrastructure and AI buildout.

🏦 6. Financials

Rising interest rates and policy changes may impact banks and fintechs.

JPMorgan Chase (JPM) – strong during rising rate environments.
Charles Schwab (SCHW) – benefits from investor optimism and capital flows.

🧱 Bonus: "Made in America" Manufacturing Push

If the next administration continues or accelerates reshoring, you might look at:

Eaton (ETN) – power management.
Generac (GNRC) – tied to grid resilience and climate-driven demand.
Enphase Energy (ENPH) – if solar incentives return.

if we go purely by the Presidential Election Cycle Theory, without regard to who's elected or what policies are implemented, the stock picks would shift slightly. Here's how it breaks down:

🔄 Presidential Election Cycle Theory (based on 100 years of market data)

Year 1 (Post-election, like 2025):
- Historically the weakest year for markets, as new policies are introduced and uncertainty is high.
- However, select sectors still do well, especially those tied to defensive industries and government spending.

📈 Sectors That Have Historically Done Well in Year 1 (like 2025)

Defense & Aerospace
- Government spending is rarely cut here, and often increases in a new administration.
- 📌 Picks: Lockheed Martin (LMT), Raytheon (RTX), Northrop Grumman (NOC)
Consumer Staples
- Investors tend to get more defensive in Year 1, favoring essentials over risk.
- 📌 Picks: Procter & Gamble (PG), Coca-Cola (KO), PepsiCo (PEP)
Utilities
- Steady cash flow, dividends, and regulation-protected businesses tend to outperform early in a presidential cycle.
- 📌 Picks: NextEra Energy (NEE), Duke Energy (DUK)
Healthcare
- Historically does well early in the cycle due to defensive nature and consistent demand.
- 📌 Picks: UnitedHealth Group (UNH), AbbVie (ABBV), Pfizer (PFE)

🧠 Less Emphasis on Risk-On Plays (at least early in Year 1)

High-growth sectors like tech, small caps, and speculative AI or biotech often lag in Year 1 of a presidency, unless there's a clear macro tailwind or stimulus policy. So under the pure cycle method, you might de-emphasize:

NVIDIA (NVDA)
Tesla (TSLA)
ARK-style innovation stocks

⏳ When Would Those Growth Stocks Shine Again?

Historically, Year 3 of a presidential cycle (i.e., 2027) is the best year for markets — that’s when risk-on names historically shine again, thanks to:

Stimulus before re-election campaigns
Low volatility
Business-friendly environments

Summary of 2025 Sector Tilt (Based on 100-Year Cycle Alone):

Sector	Reason	Example Stocks
Defense	New spending priorities, safe in all climates	LMT, RTX, NOC
Consumer Staples	Defensive, reliable earnings	PG, KO, PEP
Utilities	High dividends, stable cash flow	NEE, DUK
Healthcare	Consistent demand, defensive	UNH, ABBV, PFE

Let’s blend the Presidential Election Cycle theory with the reality of today’s innovation drivers: AI, quantum computing, and healthcare.

🧠 The Strategy:

Use the Year 1 (2025) cycle pattern as the foundation (defensives and government-aligned picks).
Overlay that with 2025’s megatrends — AI, quantum computing, and healthcare innovation.
Choose balanced exposure: stability + growth + innovation, weighted accordingly.

📊 Hypothetical 2025 Portfolio (Balanced & Thematic)

Category	Weight	Stock Picks	Rationale
Defense & Government AI	20%	Lockheed Martin (LMT) Palantir Technologies (PLTR)	Defense always gets funding in Year 1. PLTR has deep AI + Gov roots.
Consumer Staples	10%	Procter & Gamble (PG) PepsiCo (PEP)	Safe haven during economic/policy transitions.
Utilities (Green Tilt)	10%	NextEra Energy (NEE) Brookfield Renewable (BEP)	Stable dividends + clean energy upside.
Healthcare (Core)	20%	UnitedHealth (UNH) Eli Lilly (LLY)	Defensive and growth. LLY also has GLP-1 tailwind.
Healthcare (Innovative)	10%	10X Genomics (TXG) Twist Bioscience (TWST)	Genomics and synthetic biology play to long-term innovation.
AI Infrastructure (Stable)	10%	Microsoft (MSFT) NVIDIA (NVDA)	MSFT for enterprise AI/cloud, NVDA for infrastructure. Both resilient even in choppy years.
AI + Quantum Pure Plays	10%	C3.ai (AI) IonQ (IONQ)	Riskier growth, but aligned with megatrend of the decade.
Cash or Short-term Bonds	10%	BIL (Treasury ETF) or cash equivalent	Preserves dry powder for volatility and rotation into growth later in the cycle.

🧩 Optional Tilt Ideas (if you want more flavor)

Swap PEP for Costco (COST) if you want retail exposure.
Add AbbVie (ABBV) if you want more dividend-friendly healthcare.
Add Honeywell (HON) for a hybrid industrial + quantum exposure.

🎯 Portfolio Themes Summary:

Cycle-aware: Defensive posture in Year 1.
Future-aware: Allocated to the sectors leading the next wave (AI, quantum, genomics).
Balanced: Risk is spread across stability (utilities/staples), income (healthcare/defense), and innovation (AI/quantum/genomics).

Now let’s bolt on a “high-risk / high-reward” satellite portfolio that complements your core 2025 cycle-aware + future-tech portfolio.

🎯 Purpose of Satellite Portfolio:

Capture explosive upside potential from early-stage or volatile innovators.
Lean into speculative AI, quantum, biotech, and frontier tech bets.
Accept that some may not perform in Year 1 of the cycle, but could 10x+ in later years.

🚀 Speculative Satellite Portfolio (10-15% of Total Portfolio)

Stock / Ticker	Sector	Rationale
C3.ai (AI)	AI Enterprise	Early mover in AI platforms, volatile but visionary — Gov + private AI.
IonQ (IONQ)	Quantum Tech	One of the few pure-play quantum stocks, backed by AWS/Microsoft.
Recursion Pharma (RXRX)	AI + Drug Discovery	Backed by NVIDIA + using AI to map biology and accelerate pharma pipelines.
Annovis Bio (ANVS)	Alzheimer’s Biotech	Small-cap biotech chasing a huge unmet need — big swing on clinical data.
Symbotic (SYM)	Robotics/AI	AI-powered warehouse robotics, backed by Walmart and SoftBank.
ARK Genomic Revolution ETF (ARKG)	Biotech/Genomics	Access to early-stage genomics, CRISPR, and longevity companies.
BrainChip Holdings (BRCHF)	Neuromorphic AI	Super speculative — building chips modeled after the human brain.
Zapata AI (ZPTA)	Quantum-AI	Recent SPAC; combining generative AI with quantum optimization. Very high-risk.

⚠️ Notes:

These stocks/companies are more volatile and often not profitable.
Some may be thinly traded or prone to sharp corrections on news.
Meant to be a smaller piece (10-15%) of your total exposure — think moonshots.

🔧 Allocation Suggestion (If you allocate 15%)

Ticker	Allocation %
AI	2%
IONQ	2%
RXRX	2%
ANVS	2%
SYM	2%
ARKG	2%
BRCHF	1.5%
ZPTA	1.5%

ED Note:

This is not investment advice, nor am I an investment advisor. The foregoing is a report created wholly using "Deep Research" Ai using public information from 100 years of Presidential elections. It should be noted, however, that many of Wall Streets elite often refer to the "Election Cycle" metric.

Risk Level	Catalyst to Watch	Entry Price Target ($)	Stop-Loss Level ($)
High	New enterprise AI contracts, earnings growth	27.0	20.0
High	Government contracts, quantum computing adoption	10.0	7.0
High	Partnerships with pharma, AI platform development	7.0	5.0

Tuesday, March 18, 2025

Is Nvidia in the market to buy one of the first mover, pure quantum companies?

A speculative Business Case Report:

NVIDIA's Potential Partnership or Acquisition of a Quantum Computing Company

Executive Summary: NVIDIA is at the forefront of AI, high-performance computing (HPC), and GPU-accelerated workloads. As quantum computing continues to gain traction, NVIDIA may consider strategic partnerships or acquisitions in this field to enhance its position as a leader in next-generation computing. This report explores the potential for NVIDIA to partner with or acquire a quantum computing company, identifies potential targets, and examines how such a move could benefit NVIDIA's business.

1. Strategic Rationale for Entering Quantum Computing

Complementary Technologies: NVIDIA’s expertise in GPUs and accelerated computing can complement quantum computing’s strengths in optimization, simulation, and cryptography.
Market Leadership: By integrating quantum capabilities, NVIDIA can extend its leadership in AI, scientific computing, and enterprise solutions.
Infrastructure Integration:

NVIDIA’s CUDA-Q platform and GPU-accelerated quantum simulation tools suggest an existing roadmap for hybrid quantum-classical computing.
Competitive Landscape: Competitors like IBM, Google, and Amazon have already made significant strides in quantum computing, making this a necessary step for NVIDIA to remain competitive.

2. Potential Quantum Computing Companies for Partnership or Acquisition

A. IonQ

Technology: Trapped ion quantum computing, known for its long coherence times and scalability.
Existing Collaborations: Works with major cloud providers like AWS, Azure, and Google Cloud.
Strategic Fit: Integration with NVIDIA’s AI and HPC solutions could accelerate quantum-enhanced machine learning.

B. Rigetti Computing

Technology: Superconducting qubits, with an open-access quantum cloud platform.
Existing Collaborations: Partnerships with government agencies and enterprise clients.
Strategic Fit: Could leverage NVIDIA’s hardware acceleration to improve quantum circuit simulations and error correction.

C. D-Wave Systems

Technology: Quantum annealing, best suited for optimization problems.
Existing Collaborations: Worked with NASA, Google, and enterprise clients for quantum-assisted optimization.
Strategic Fit: D-Wave’s annealing approach could integrate with NVIDIA’s AI for enhanced optimization and logistics solutions.

D. Quantinuum (Honeywell Quantum Solutions + Cambridge Quantum)

Technology: Ion-trap quantum computing and quantum software stack.
Existing Collaborations: Strong government and enterprise partnerships.
Strategic Fit: Offers robust quantum security and hybrid computing capabilities that could benefit NVIDIA’s broader AI and HPC initiatives.

E. PsiQuantum

Technology: Photonic quantum computing, leveraging silicon photonics for scalability.
Existing Collaborations: Funded by major investors and working toward fault-tolerant quantum computing.
Strategic Fit: Alignment with NVIDIA’s interest in silicon photonics for AI data centers.

3. How Quantum Computing Can Advance NVIDIA’s Business

Accelerated AI and Machine Learning: Hybrid quantum-classical computing can enable faster model training and more efficient AI algorithms.
Supercomputing and Simulations: Quantum computing could enhance NVIDIA’s presence in high-end scientific and financial modeling applications.
Cybersecurity and Cryptography: Post-quantum cryptography solutions can be integrated into NVIDIA’s data security offerings.
Supply Chain and Optimization: Quantum optimization algorithms can improve logistics, chip manufacturing, and data center operations.
Software Ecosystem Expansion: CUDA-Q and other NVIDIA software tools can be extended to quantum-classical hybrid computing, opening new revenue streams.

4. Challenges and Risks

Technology Maturity: Quantum computing is still in its early stages; commercial viability remains uncertain.
Regulatory Hurdles: Any acquisition, especially of a U.S. or foreign quantum company, may face government scrutiny.
Integration Complexity: Aligning quantum computing hardware and software with NVIDIA’s existing ecosystem may take years.
Competition: IBM, Google, and Microsoft are also aggressively expanding in quantum computing, potentially limiting NVIDIA’s strategic moves.

As of January 31, 2025, NVIDIA reported cash and cash equivalents totaling approximately $43.21 billion, a significant increase from $25.98 billion in 2024 and $13.30 billion in 2023. Morningstar Tools+2CompaniesMarketCap+2Macrotrends+2

This substantial cash reserve positions NVIDIA favorably for potential acquisitions. Considering the quantum computing companies previously discussed:Reuters

IonQ: With a market capitalization around $6.4 billion. The Motley Fool
Rigetti Computing: Valued at approximately $2.1 billion. TradingView
D-Wave Systems: Market capitalization details are not specified, but the company's stock has seen significant recent increases.
PsiQuantum: Valued at approximately $3.15 billion as of July 2021. en.wikipedia.org

Given these valuations, NVIDIA's cash reserves are sufficient to acquire any of these companies outright, should it choose to do so.

(Ed note: an acquisition of one of these companies would only constitute a "rounding error" for Nvidia)

5. Conclusion and Recommendation

Given the increasing convergence of AI, HPC, and quantum computing, NVIDIA should strongly consider acquiring or partnering with a quantum computing company. The best options for acquisition appear to be IonQ, Rigetti Computing, or PsiQuantum, given their scalability potential and technology alignment with NVIDIA’s roadmap. Alternatively, forming a strategic partnership with D-Wave or Quantinuum could allow NVIDIA to integrate quantum computing capabilities without the full risks of acquisition.

A well-executed quantum strategy will not only future-proof NVIDIA against emerging computing paradigms but also position it as the industry leader in AI-accelerated quantum computing solutions.

Monday, March 17, 2025

The immediate future of computing isn’t Quantum VS Classical computing, it is BOTH, and, Nvidia may have the key!

Merging Quantum and Classical Computing Is Closer Than You Think

Executive Summary

The integration of quantum and classical computing is rapidly advancing, driven by strategic partnerships between quantum hardware companies and established leaders in classical high-performance computing (HPC). The collaboration between Rigetti Computing and Nvidia, along with contributions from IONQ, demonstrates how quantum computing is transitioning from theoretical research to practical hybrid solutions. Nvidia’s CUDA Quantum (formerly CUDA-Q) is a key enabler in this transformation, offering a hardware-agnostic and GPU-accelerated framework for quantum-classical computing.

This report examines the significance of Nvidia’s CUDA Quantum, how Rigetti and IONQ contribute to the hybrid computing landscape, and the broader market implications for businesses and investors.

1. The Role of CUDA Quantum in Hybrid Computing

What Is CUDA Quantum?

CUDA Quantum is Nvidia’s open-source hybrid computing framework designed to integrate quantum and classical computing seamlessly. By allowing developers to execute quantum circuits alongside classical code, CUDA Quantum accelerates quantum simulations, machine learning, and AI applications using Nvidia’s powerful A100 and H100 GPUs.

Key Features:

Hardware-Agnostic Integration: Supports various quantum backends, including Rigetti, IONQ, and Quantinuum.
GPU-Accelerated Quantum Simulations: Uses Nvidia’s cuQuantum SDK to improve quantum circuit validation and noise modeling.
Flexible Programming Models: Supports Python, C++, and CUDA-based hybrid workflows.
Error Correction & Mitigation: Enables advanced quantum error reduction techniques, which are critical for near-term practical applications.

Why It Matters: CUDA Quantum acts as a bridge, bringing quantum computing closer to enterprise adoption by combining classical HPC scalability with quantum-enhanced algorithms.

2. Rigetti’s Contribution to Hybrid Computing

Rigetti Computing, a leader in superconducting quantum processors, is leveraging CUDA Quantum to enhance hybrid computing capabilities.

Rigetti’s Key Contributions:

Quantum Cloud Services (QCS): Provides a platform for running hybrid quantum-classical workloads.
QPU-HPC Integration: Utilizes Nvidia GPUs to accelerate quantum simulations before deployment on real hardware.
Variational Quantum Algorithms (VQAs): Optimizes applications in machine learning, finance, and materials science.
Error Correction Research: Uses Nvidia’s cuQuantum SDK to improve quantum noise mitigation.

Investment Takeaway:

Rigetti’s partnership with Nvidia strengthens its position in hybrid quantum architectures, making it a strong candidate for enterprise adoption.
By leveraging Nvidia’s dominant AI infrastructure, Rigetti gains an edge in transitioning quantum computing from experimental to commercial use cases.

3. IONQ’s Input into CUDA Quantum

While Rigetti focuses on superconducting qubits, IONQ specializes in trapped-ion quantum computers, which offer high-fidelity quantum operations.

IONQ’s Key Contributions:

Trapped-Ion Quantum Hardware: Provides one of the most advanced quantum computing architectures.
Hybrid Quantum-Classical Workflows: Uses CUDA Quantum to enhance quantum state simulations and error correction.
Quantum AI Research: Nvidia and IONQ collaborate on AI-driven quantum applications, such as quantum-enhanced neural networks.
Cloud Deployments: CUDA Quantum enables IONQ to scale its cloud-accessible QPUs for business applications.

Investment Takeaway:

IONQ is positioned to benefit from Nvidia’s enterprise AI ecosystem, increasing its market reach.
The integration of trapped-ion technology into CUDA Quantum signals a long-term hybrid quantum future.

4. Market Implications & Investment Outlook

Why This Partnership Is a Game-Changer

Quantum-AI Convergence: Quantum computing is being integrated into AI and supercomputing, paving the way for quantum-enhanced machine learning.
Bridging the Quantum-Classical Divide: Hybrid computing frameworks like CUDA Quantum allow businesses to adopt quantum computing incrementally.
Competitive Positioning:
- Rigetti: Strengthens its standing in HPC-quantum integration.
- IONQ: Expands its role in quantum-enhanced AI applications.
- Nvidia: Secures its place as the leading enabler of quantum-classical acceleration.

Competitive Landscape

IBM, Google, and Microsoft are also investing in hybrid quantum computing, but Nvidia’s dominance in GPU-based AI gives it a unique advantage.
AWS and Azure Quantum are integrating hybrid solutions, but CUDA Quantum provides a more standardized and developer-friendly platform.

Investment Considerations

Near-Term Opportunities: Companies utilizing hybrid quantum-classical workflows are likely to see increased adoption before full-scale quantum advantage is reached.
Long-Term Growth: Nvidia’s continued investment in quantum acceleration ensures that quantum computing will be an integral part of future AI and cloud computing ecosystems.
Early Adopters: Businesses adopting CUDA Quantum today will have a first-mover advantage in sectors like finance, healthcare, and materials science.

Conclusion: The Quantum-Classical Merger Is Closer Than You Think

The integration of quantum and classical computing is no longer just a theoretical concept—it is actively shaping the future of high-performance computing, AI, and business applications. Nvidia’s CUDA Quantum is the linchpin of this transformation, enabling companies like Rigetti and IONQ to accelerate the development and deployment of hybrid quantum solutions.

Key Takeaways:

Nvidia’s CUDA Quantum is the de facto hybrid quantum-classical platform.
Rigetti’s QCS and IONQ’s trapped-ion technology are being enhanced by Nvidia’s HPC ecosystem.
Investors should watch for increasing enterprise adoption of hybrid quantum computing solutions.

Final Thought:

The line between quantum and classical computing is blurring faster than anticipated. Businesses and investors who position themselves today will be at the forefront of the quantum revolution in AI and HPC.

Recommended Actions for Investors

Monitor Nvidia’s CUDA Quantum updates for emerging enterprise adoption.
Assess Rigetti’s and IONQ’s partnerships to identify growth catalysts.
Consider companies integrating hybrid quantum solutions in AI, finance, and biotech.

The future of computing isn’t just quantum—it’s quantum and classical, working together.

Wednesday, March 12, 2025

Practical business problem solved proving quantum supremacy says D-Wave Quantum!

D-Wave Quantum Inc. (NYSE: QBTS) announced today that its Advantage2 annealing quantum computer has achieved a significant milestone in quantum computing by outperforming one of the world's most powerful classical supercomputers in solving complex magnetic materials simulation problems. This accomplishment, detailed in the peer-reviewed journal Science, represents the first demonstration of quantum computational supremacy on a practical, real-world problem. ft.com+9stocktitan.net+9Benzinga+9

In the study, D-Wave's quantum computer simulated the behavior of magnetic materials—a task that would have taken a classical supercomputer nearly one million years to complete. This breakthrough is particularly significant for fields such as materials discovery, medical imaging, electronics, and superconductors, where understanding the quantum nature of magnetic materials is crucial. Barron's+4stocktitan.net+4wsj.com+4Benzinga+4stocktitan.net+4stocktitan.net+4

The Advantage2 system used in this research was fabricated in collaboration with SkyWater Technology, a U.S.-based semiconductor manufacturer. This partnership underscores the importance of domestic manufacturing in advancing global technology leadership. Barron's+5businesswire.com+5businesswire.com+5stocktitan.net+3Benzinga+3businesswire.com+3

Following the announcement, D-Wave's stock experienced a notable increase, reflecting investor optimism about the company's technological advancements and their potential applications across various industries. investors.com

D-Wave's Quantum Supremacy Claim Sparks Industry Buzz

wsj.com

D-Wave Claims 'Quantum Supremacy,' Beating Traditional Computers

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Solving practical technical problems for Businesses and Science

D-Wave's quantum supremacy claim revolves around solving a magnetic materials simulation problem, specifically related to the quantum dynamics of spin glasses. This type of problem is notoriously difficult for classical supercomputers to handle due to its complex, high-dimensional energy landscapes and the need to track intricate quantum interactions over time.

The Problem: Simulating Quantum Spin Glasses

Spin glasses are disordered magnetic systems where the spins (tiny magnetic moments of atoms) are arranged in a way that leads to frustration—meaning the system cannot settle into a simple, low-energy state. Understanding the behavior of spin glasses is crucial for various applications in materials science, optimization, neuroscience, and artificial intelligence.

Why Is This Problem Hard for Classical Computers?
- The problem involves tracking quantum fluctuations and entanglement in a many-body system.
- A classical supercomputer would need to simulate a vast number of possible configurations and their energy states, leading to an exponential scaling problem—the number of possibilities grows too large to compute within a reasonable timeframe.
- Prior classical methods use approximate algorithms that introduce errors or take an infeasibly long time to run.

How D-Wave’s Quantum Computer (Advantage 2) Solved It

D-Wave used its Advantage2 annealing quantum computer, which is specifically designed to tackle optimization and combinatorial problems efficiently. The researchers compared their quantum annealer against state-of-the-art classical algorithms running on one of the world’s most powerful supercomputers.

Key Findings:

Quantum Speedup:
- The quantum annealer significantly outperformed classical methods in simulating the coherent quantum dynamics of spin glasses.
- The classical simulations would have taken nearly one million years, whereas D-Wave’s system solved it in a feasible amount of time.
First "Useful" Quantum Supremacy Demonstration:
- Unlike previous supremacy claims (e.g., Google's 2019 claim, which solved a random sampling problem with little real-world utility), D-Wave’s problem has practical applications in physics, chemistry, and engineering.
Material Science and Industry Applications:
- Understanding spin glasses can lead to advancements in designing superconductors, better memory storage devices, and more efficient electronics.
- The experiment also lays the foundation for future quantum simulations of chemical reactions, drug interactions, and advanced AI models.

Why This Matters

This result is groundbreaking because:

It demonstrates quantum advantage on a real-world problem rather than an artificially constructed task.
It validates annealing-based quantum computing as a useful approach for solving physics and optimization problems.
It could accelerate progress in multiple scientific and industrial domains, from new material discovery to complex optimization tasks in logistics, AI, and cybersecurity.

This achievement positions D-Wave’s approach to quantum computing as a strong contender in the race for practical quantum applications.

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Will Nvidia and D-Wave collaborate in future?

Ed Note:

D-Wave Quantum Inc. and NVIDIA have engaged in discussions about the integration of quantum processing units (QPUs) and graphical processing units (GPUs). In January 2025, D-Wave's CEO, Dr. Alan Baratz, addressed comments made by NVIDIA's CEO, Jensen Huang, regarding the timeline for practical quantum computing applications. Dr. Baratz emphasized that D-Wave's annealing quantum computing solutions are already commercially available and solving real-world problems. He also expressed openness to collaborating with companies like NVIDIA to explore the potential of combining QPUs and GPUs.
While no formal partnership has been announced, both companies have acknowledged the potential benefits of integrating their respective technologies. NVIDIA has been actively involved in quantum computing research, particularly in simulating quantum annealers, a type of quantum computer that D-Wave specializes in. In July 2024, NVIDIA's supercomputers were utilized to validate pathways toward the commercialization of quantum computing, specifically focusing on quantum annealing methods. blogs.nvidia.com
These developments suggest a mutual interest in exploring collaborative opportunities between D-Wave and NVIDIA, aiming to enhance the capabilities of both quantum and classical computing systems.

Tuesday, March 11, 2025

Nvidia's interest and investment in Recursion Pharmaceuticals (RXRX) in 2025 could be a game changer for this small-cap!

Recursion Pharmaceuticals (NASDAQ: RXRX) is a clinical-stage biotechnology company that integrates advanced technologies across biology, chemistry, automation, data science, and engineering to decode complex biological systems. Here's an updated overview of the company's financials, partnerships, technological advancements, product pipeline, and other pertinent information:

Financial Overview

Cash Position: As of December 31, 2024, Recursion reported cash, cash equivalents, and restricted cash totaling $603.0 million, up from $401.4 million on the same date in 2023. ir.recursion.com
Revenue: The company achieved total revenue of $83 million for the fiscal year 2024, reflecting a strong financial performance. tipranks.com
Research and Development Expenses: R&D expenses were $74.6 million for Q3 2024, up from $70.0 million in Q3 2023, indicating continued investment in platform expansion and upgrades. globenewswire.com
Net Loss: The net loss for Q3 2024 was $95.8 million, compared to $93.0 million in Q3 2023, reflecting ongoing investments in research and development. globenewswire.com

Strategic Partnerships

NVIDIA: In July 2023, NVIDIA invested $50 million in Recursion to accelerate the development of AI foundation models for biology and chemistry. This collaboration leverages Recursion's extensive proprietary dataset and NVIDIA's cloud services, including the DGX™ Cloud and BioNeMo platform, to enhance drug discovery capabilities. en.wikipedia.org
Roche and Genentech: In December 2021, Recursion entered into a partnership with Roche and its subsidiary Genentech, potentially worth up to $12 billion, to advance therapies in neuroscience and other areas. en.wikipedia.org
Bayer: The company has a strategic collaboration with Bayer focusing on oncology research, building upon a previous partnership targeting fibrotic diseases. en.wikipedia.org
Exscientia Acquisition: In August 2024, Recursion acquired UK-based biotechnology company Exscientia for $688 million, adding a technology-enabled clinical pipeline and precision chemistry capabilities. globenewswire.com+1en.wikipedia.org+1

Technological Infrastructure

Recursion OS: The company's proprietary operating system integrates wet-lab and dry-lab biology experiments, enabling the generation of massive datasets to map and navigate complex biological relationships. sec.gov
BioHive-2 Supercomputer: In May 2024, Recursion completed BioHive-2, an NVIDIA-powered AI supercomputer comprising 63 DGX H100 systems with a total of 504 NVIDIA H100 Tensor Core GPUs. Ranked #35 in the TOP500 list of the world's most powerful supercomputers, BioHive-2 significantly enhances Recursion's computational capabilities, facilitating more efficient training of large-scale AI models.

Product Pipeline and Clinical Developments

REC-994: This experimental drug targets cerebral cavernous malformation (CCM), a rare brain-related condition. In a mid-stage study reported in September 2024, REC-994 demonstrated safety and tolerability. MRI-based data indicated that the highest dose reduced the number of lesions. However, improvements reported by patients or doctors were not observed at the end of the 12-month treatment period. Recursion plans to meet with the U.S. Food and Drug Administration to discuss further clinical studies. Reuters
Clinical Trial Outlook: Recursion anticipates seven clinical trial readouts over the next 18 months for its programs and approximately ten readouts collectively over the same period, including those from the Exscientia acquisition. globenewswire.com+1en.wikipedia.org+1

Intellectual Property

Patent Portfolio: As of February 2025, Recursion holds a total of 149 patents globally, with 58 granted. Notably, over 78% of these patents remain active. The majority are filed in the United States, followed by Europe and Canada.

Conclusion

Recursion Pharmaceuticals continues to leverage its robust financial position, strategic partnerships, and advanced technological infrastructure to pioneer AI-driven drug discovery and development. The company's expanding patent portfolio and active clinical pipeline underscore its commitment to transforming the pharmaceutical industry through innovative approaches to complex diseases.

Nvidia-backed Recursion's shares fall on mixed data for rare disorder drug

Reuters

Nvidia-backed Recursion's shares fall on mixed data for rare disorder drug