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BigBear.ai vs. IonQ: Weighing Whether to Invest in the Artificial Intelligence Company or the Quantum Computing Giant - The Motley Fool
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BigBear.ai vs. IonQ: Weighing Whether to Invest in the Artificial Intelligence Company or the Quantum Computing Giant - The Motley Fool

Choosing between a software-driven artificial intelligence company and a quantum computing pioneer requires weighing utility against technical potential. Investors have this choice in BigBear.ai (BBAI +1.77%) and IonQ (IONQ -0.24%) when searching for high-growth tech opportunities.BigBear.ai provides specialized artificial intelligence solutions for supply chains and defense, while IonQ builds the hardware necessary for a quantum computing future. Both companies are in early stages of development, offering investors exposure to different corners of the emerging technology landscape through distinct business models.The case for BigBear.aiBigBear.ai offers decision intelligence solutions tailored for complex environments like supply chains, autonomous systems, and security at airports through its biometrics solutions. The company generates more than 50% of its revenue from a few key customers, including major contracts with the U.S. Department of Defense and federal intelligence agencies. Note that customer concentration like this adds a layer of risk to the business, as revenue depends heavily on government budget cycles.In its 2025 fiscal year (FY), revenue reached $127.7 million, indicating a decline of 19.3% compared to the previous year. The company reported a net loss of $293.9 million during this period, which was a slight narrowing from the $295.5 million net loss seen in FY 2024. While the software model allows for potential scalability, the recent downward trend in revenue suggests the business is facing challenges in expanding its commercial and government footprint.As of its December 2025 balance sheet, BigBear.ai has a debt-to-equity ratio of zero, signifying it carries no significant debt relative to its shareholder equity. The current ratio is 1.8x, which measures a company's ability to cover its short-term debts with short-term assets. Free cash flow for FY 2025 was negative $46.3 million, calculated as cash from operations minus capital expenditures,

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RIKEN protein model reaches 12,635 atoms using quantum-classical computingquantum-computing

RIKEN protein model reaches 12,635 atoms using quantum-classical computing

A research collaboration between Cleveland Clinic, RIKEN, and IBM has reached a new benchmark in molecular modeling, simulating a protein containing 12,635 atoms, the largest ever achieved using quantum computers, the company says. The team’s success, detailed in work initially published in May 2026, combines the power of quantum and classical computing in a framework they call quantum-centric supercomputing, with calculations running on IBM Quantum Heron processors at both Cleveland Clinic and RIKEN, alongside Japan’s Fugaku and Miyabi-G supercomputers. To achieve these results, the team first scaled their method roughly 40 times while also achieving 210 times improvement in accuracy, and then advanced the work further. This achievement has earned the team a place as a finalist for the 2026 ACM Gordon Bell Prize, recognizing outstanding innovation in high-performance computing, and targets improvements in drug discovery by more accurately computing atomic energies during biological processes. The team validated the workflow on JHPC-quantum GPU supercomputer “ROQUO,” RIKEN’s newest system, eliminating the need for complex manual operations and data transfers. Quantum-Classical Methods Simulate 12,635-Atom Protein The simulation achieved a 210-fold improvement in accuracy, accomplished less than one year after the team first scaled their method roughly 40 times. This leap in precision stems from refinements to embedded wavefunction methods at Cleveland Clinic, adapted to address the specific challenges of this larger system. The researchers coupled these advancements with sample-based quantum diagonalization developed jointly by IBM and RIKEN, a technique previously highlighted on the cover of Science Advances. This combined approach, termed quantum-centric supercomputing, uses the strengths of both computational paradigms to tackle previously intractable problems in molecular modeling. RIKEN’s commitment to hybrid quantum-classical computing is underscored by its st

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