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Cleveland Clinic, RIKEN, and IBM Model a 12,635-Atom Protein – the Largest Known to Be Simulated with Quantum Computers

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Milestone simulation of biologically meaningful molecules expands quantum-centric supercomputing’s role as a scientific tool

YORKTOWN HEIGHTS, N.Y. and CLEVELAND, May 5, 2026 /PRNewswire/ — Scientists at Cleveland Clinic, RIKEN, and IBM (NYSE: IBM) have used IBM quantum computers and two of the world’s most powerful supercomputers to simulate protein complexes spanning up to 12,635 atoms. These are the largest-known simulations of biologically meaningful molecules performed with quantum hardware yet, and signal that quantum computers are maturing into useful scientific tools which can help solve fundamental problems in biology, chemistry, and life sciences.

The results were achieved in part by an innovative algorithm that optimizes how quantum and classical computers can work together, a framework known as quantum-centric supercomputing. Using this approach, the team captured the behavior of two biochemically relevant proteins that are roughly 40 times larger than what this same method could initially achieve just six months ago. Additionally, the accuracy of the simulations in a key step of the workflow improved by up to 210 times over this same period.

The decision to explore if quantum computers could offer value in the simulation of protein complexes was motivated by challenges faced today by researchers when studying how a drug candidate could bind to a protein. This can be one of the most difficult and expensive problems in life sciences research, and one that today’s existing computational methods have struggled to exactly solve as molecules increase in size. Doing so accurately and early in the discovery process could meaningfully shorten drug development timelines that currently can stretch over a decade and require substantial investment to produce a single medicine.

“This work marks an important advance and underscores quantum computing’s emerging role on systems of relevance to drug discovery,” said Kenneth Merz, Ph.D., lead author of the study and staff scientist in Cleveland Clinic’s Computational Life Sciences Department. “By crossing the 12,000-atom barrier, we have significantly expanded the scale of biologically meaningful molecular simulations possible with quantum computing and demonstrated a framework for applying these methods to scientifically relevant problems at a larger scale.”

“For years, quantum computing has been a promise. Now, quantum computers are producing results that matter to science,” said Jay Gambetta, Director of IBM Research and IBM Fellow. “The systems we simulated here are the kind of molecules that biologists and chemists work with in the real world. Quantum computers are no longer proving they are viable tools – they are proving they can contribute meaningful results in quantum-centric supercomputing architectures.”

The breakthrough research, reported in a pre-print study, builds on a series of milestones from the three institutions. This includes work on the cover of Science Advances that introduced techniques to model electronic states in molecules, first demonstrated on iron sulfides, and more recently, the 303-atom benchmark molecule called Trp-cage – the first-known full quantum-centric simulation made of 20 amino acids.

Quantum and Classical Computers, Working in Tandem

This approach – what IBM calls quantum-centric supercomputing – pairs quantum processors with classical computers so each computational tool can solve the parts of a problem where it excels. In this work, classical computers deconstructed the protein-ligand complexes into computable fragments. IBM’s 156-qubit IBM Quantum Heron processors, running within the IBM quantum computers at both Cleveland Clinic in the United States and RIKEN in Japan, calculated the quantum-mechanical behavior of those pieces in tandem with two of the most powerful classical supercomputers – Fugaku at RIKEN and Miyabi-G, operated by the University of Tokyo and the University of Tsukuba. The strength of IBM’s quantum hardware was essential to the accuracy and success of the computation, which required up to 94 qubits running nearly 6,000 quantum operations within certain parts of the simulation. Results were reassembled on classical computers to obtain a complete representation of the molecule.

As published on arXiv, the jump in scale was made possible by both algorithmic innovation and access to cutting-edge computing infrastructure. The novel quantum-classical hybrid algorithm, coined EWF-TrimSQD, dramatically reduced computational overhead and accelerated the ability to directly represent the chemistry of these molecular systems on quantum hardware. As a result, the frontier for what is possible with quantum-centric supercomputing has been pushed forward to previously inaccessible molecule sizes, and there is a clear path to further increase the size and accuracy of such calculations.

A Step Towards Drug Discovery

The team views this work as a starting point. Looking ahead, the ability to scale simulations of molecular systems with accuracy is a step towards helping researchers better predict how medicines may interact with protein targets. Computational improvements in drug discovery rest on two fundamental capabilities: first, modeling the movement of atoms as biological processes unfold; and second, accurately computing their energies, for which these results provide evidence that quantum‑centric supercomputing can support.

As quantum computers advance, integrating them into computational workflows could offer higher accuracy in energy calculations at larger scales, and potentially open the door to simulating enzyme catalysts, drug mechanisms, and other molecular behaviors that today can only be studied through experimentation.

More broadly, this breakthrough marks a shift in what quantum computing means to science. For most of its history, the field of quantum computation has measured progress in qubits, gates, and error rates. Now, its capabilities can also be measured by the size and significance of the problems it can help to solve.

For more information on this milestone, visit: https://www.ibm.com/quantum/blog/cleveland-clinic-riken-chemistry

Research Support

This research is supported by NEDO (New Energy and Industrial Technology Development Organization), an organization under the jurisdiction of Japan’s Ministry of Economy, Trade and Industry (METI)’s “Research and Development of Quantum-Supercomputers Hybrid Platform for Exploration of Uncharted Computable Capabilities” (Project Leader: Mitsuhisa Sato) as part of the “Project for Research and Development of Enhanced Infrastructures for Post 5G Information and Communications Systems (JPNP20017).”

About IBM

IBM is a leading global hybrid cloud and AI, and business services provider, helping clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Thousands of governments and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity and service.
For more information, visit https://research.ibm.com.

About Cleveland Clinic

Cleveland Clinic is a nonprofit multispecialty academic medical center that integrates clinical and hospital care with research and education. Founded in 1921 by four renowned physicians with a vision of providing outstanding patient care based upon the principles of cooperation, compassion and innovation, Cleveland Clinic has pioneered many medical breakthroughs, including coronary artery bypass surgery and the first face transplant in the United States. Cleveland Clinic is consistently recognized in the U.S. and throughout the world for its expertise and care. Among Cleveland Clinic’s 83,000 employees worldwide are more than 6,600 salaried physicians and researchers, and 21,900 registered nurses and advanced practice providers, representing 140 medical specialties and subspecialties. Cleveland Clinic is a 6,725-bed health system that includes a 173-acre main campus near downtown Cleveland, 23 hospitals, 300 outpatient facilities, including locations in northeast Ohio; Florida; Las Vegas, Nevada; Toronto, Canada; Abu Dhabi, UAE; and London, England. In 2025, there were 15.9 million outpatient encounters, 343,000 hospital admissions and observations, and 336,000 surgeries and procedures throughout Cleveland Clinic’s health system. Visit us at clevelandclinic.org. Follow us at x.com/CleClinicNews. News and resources are available at newsroom.clevelandclinic.org.

Media contacts

Brittany Forgione
IBM
Brittany.Forgione@ibm.com

Erin Angelini
IBM Research Communications
edlehr@us.ibm.com

Alicia Reale-Cooney
Cleveland Clinic
realeca@ccf.org  
216.408.7444

 

 

 

SOURCE IBM

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Toku launches Makimoto Flows, a visual builder for speech AI pipelines, taking its open-source initiative beyond transcription

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Developers can chain transcription, summarisation and call tagging on one canvas, test each step and export the pipeline as code, with every step processed in Singapore

SINGAPORE, Oct. 21, 2026 /PRNewswire/ — Toku Ltd. (SGX: TKU), a Singapore-headquartered AI-powered customer experience (CX) platform, has launched Makimoto Flows (“Flows”), a visual builder within its open-source conversational AI initiative where developers assemble speech AI pipelines block by block and test each stage on a recorded call. Flows is now live at makimoto.ai.

On the Flows canvas, developers connect blocks to build a speech AI pipeline and test each step individually. The Transcribe block converts audio into text using Kawa, the Summarise block generates a topic and short summary from the transcript, and the Tags block classifies each call across seven categories, including customer sentiment. Developers can see how audio moves from transcription to analysis, and control how each stage connects and runs. Every block runs in Singapore, so audio, transcripts and the resulting analysis stay in-country.

The Chained Analysis starter template puts these blocks together in one click, and developers can adjust any block and rerun it to compare results. Each block maps to a Makimoto API endpoint, and any flow can be exported as ready-to-run Python code, so developers can take the same capabilities into their own code for applications such as call recaps and call triage.

“Developers should have control over how their voice AI works, from the models they use to the way each stage connects. That is the principle behind Makimoto. Flows puts the orchestration layer in front of them: they can build a pipeline, run a recorded call through it and see what each step produces before anything reaches their customers. Models will keep changing. The ability to compose them, and to know where they run, is what lasts,” said Thomas Laboulle, Founder and CEO at Toku.

Flows builds on the composable architecture Toku set out when it introduced Makimoto in April 2026, and takes the initiative beyond transcription. Kawa, released on schedule on 1 July 2026, established the transcription layer through a Singapore-hosted API; summarisation and tagging endpoints followed in September; Flows now lets developers compose them visually. Next, Makimoto plans to add audio preparation blocks, starting with noise filtering, giving developers more control over how recordings are processed before transcription.

By pairing open-source development with enterprise-grade deployment, Makimoto complements Toku’s existing customer experience platform and supports long-term innovation opportunities across the Group’s AI roadmap.

Developers can create a free account at makimoto.ai, open the Chained Analysis template and run a sample recording, or one of their own call recordings, through it; each account includes 1,000 free minutes. Feedback reaches the Makimoto team directly from the portal.

About Toku

Headquartered in Singapore, Toku Ltd. (SGX Catalist: TKU) is a cloud-native, AI-powered customer experience platform purpose-built for enterprises operating in complex, multi-market environments. With deep roots in the APAC region and an expanding global footprint, Toku’s modular 360° CX Platform orchestrates customer interactions across voice, chat, email and digital channels while managing regulatory, linguistic and infrastructure complexity at scale.

Built on end-to-end ownership of its technology stack, from carrier-grade connectivity to AI applications, Toku delivers enterprise-grade security, reliability and deployment flexibility in commercial cloud, private data centres and hybrid environments. Its AI capabilities include transcription, summarisation, sentiment analysis, conversation analytics and governed virtual agents, designed to integrate seamlessly with enterprise systems and customer data.

Trusted by leading enterprises and public-sector organisations, Toku helps organisations streamline operations, scale customer engagement and deliver consistent experiences in fragmented markets worldwide.

For more information about Toku, visit toku.co.

About Makimoto

Makimoto is Toku’s open-source initiative, operated through Makimoto Technology Pte Ltd, a wholly owned subsidiary of the Toku Group, dedicated to building composable conversational AI infrastructure for Asia-Pacific. Its releases include Makimoto Kawa, a Singapore-hosted transcription API; summarisation and tagging endpoints; and Makimoto Flows, a visual builder for composing speech AI pipelines. For more information about Makimoto, visit makimoto.ai.

Forward-Looking Statements

This press release contains forward-looking statements regarding Toku’s expansion plans, business strategy and planned product releases. These statements are based on current expectations and assumptions and are subject to risks and uncertainties that could cause actual results to differ materially. Toku undertakes no obligation to update these statements to reflect subsequent events or circumstances.

Sponsor’s Statement

Toku Ltd. (the “Company”) was listed on Catalist of the Singapore Exchange Securities Trading Limited (the “Exchange”) on 22 January 2026. The initial public offering of the Company was sponsored by PrimePartners Corporate Finance Pte. Ltd. (the “Sponsor”). This press release has been reviewed by the Sponsor. It has not been examined or approved by the Exchange and the Exchange assumes no responsibility for the contents of this press release, including the correctness of any of the statements or opinions made or reports contained in this press release. The contact person for the Sponsor is Ms. Ng Shi Qing, 16 Collyer Quay, #10-00 Collyer Quay Centre, Singapore 049318, sponsorship@ppcf.com.sg.

Investor Relations Contact:
investor.relations@toku.co

Developers and Partners:
contact@makimoto.ai  

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SOURCE Toku Ltd.

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Conscious Spark LLC Launches Alphimiya® Neuro-Recalibration Framework Designed to Resolve C-Suite Revenue Plateaus

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New research-backed neuro-recalibration framework targets the autonomic nervous system’s threat response to managing high financial amounts, offering enterprise leaders a biological pathway to scaling.

ANTALYA, Turkey and ALBUQUERQUE, N.M., Oct. 21, 2026 /PRNewswire/ — Conscious Spark LLC, a research and advisory firm specializing in applied neuroscience for executive leadership, today announced the official launch of Alphimiya®, a proprietary C-suite neuro-recalibration framework designed to resolve corporate revenue plateaus by upgrading the biological capacity of enterprise decision-makers.

Developed to address the root causes of stalled enterprise growth, the Alphimiya® framework targets the human autonomic nervous system’s subconscious threat response to managing high financial amounts. When commercial leaders and CEOs attempt to scale past historical capital thresholds without recalibrating their stress response, the body’s natural survival mechanism triggers decision fatigue, strategic risk aversion, and systemic self-sabotage. Alphimiya® recalibrates this biological safety brake, enabling executive teams to hold, absorb, and scale larger financial volumes without physiological or operational friction.

“A corporate revenue plateau is rarely an operational or marketing failure; it is a biological safety brake embedded within executive leadership,” stated Dr. Ahmed Al-Nashi, Founder of Conscious Spark LLC. “When managing high financial amounts triggers an underlying physical stress response, the enterprise subconsciously contracts to remain in its perceived safe zone. Alphimiya® removes that biological friction, allowing C-level leaders to multiply revenue with calm, biological authority.”

The Alphimiya® framework restructures executive performance across three core operational pillars:

Sovereign Enterprise Scaling: Expands the nervous system’s tolerance for high-stakes capital, allowing leadership teams to scale revenue without experiencing executive burnout.

High-Value Deal Execution: Regulates autonomic stress responses during multi-million-dollar negotiations and volatile market entries, eliminating hesitation under pressure.

Restored Strategic Clarity: Removes chronic decision fatigue across C-suite teams, restoring mental focus and strategic presence inside and outside the boardroom.

By recalibrating the autonomic nervous system’s response to high capital exposure, Alphimiya® removes the subconscious biological brakes that lock corporate revenue at a standstill. Senior C-level executives and enterprise leadership teams seeking to evaluate their organization’s biological capacity can access the official executive briefing, case studies, and framework assessment directly at https://alphimiya.co/.

About Conscious Spark LLC

Conscious Spark LLC is a U.S.-registered firm specializing in executive education, training, and strategic performance consulting. Pioneering applied neuroscience for C-level leaders, founders, and commercial decision-makers, the firm utilizes its proprietary Alphimiya® methodology to enable leadership teams to recalibrate biological stress responses, resolve revenue ceilings, and build scalable corporations.

Media Relations Team
Conscious Spark LLC
Email: hello@consciousspark.online 
Website: https://alphimiya.co/

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SOURCE Conscious Spark LLC

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Daffodil Software Brings Multilingual Conversational AI to Aadhaar’s Udai Mascot

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GURUGRAM, India, Oct. 21, 2026 /PRNewswire/ — Daffodil Software showcased an AI-powered conversational experience featuring UIDAI’s Udai mascot at Aadhaar Samvaad 2026. Developed by Daffodil Software, the assistant is designed to help users access Aadhaar-related information through natural conversation, using official UIDAI as its reference knowledge base.

Daffodil Software has developed Udai, an AI-powered virtual mascot that helps users get clear, reliable answers about Aadhaar simply by talking to it. The assistant was showcased at Aadhaar Samvaad 2026, held in Kolkata on 29 September, coinciding with the 17th Aadhaar Day, where visitors watched it listen, respond, and gesture in real time in their own language.

For most people, questions about Aadhaar come up in daily life, and they usually need answers fast. Which documents do I need for an address change? How much does an update cost? How do I link Aadhaar to my bank account or mobile number? The answers exist, but finding them usually means working through long help pages and documents.

 Udai is designed to answer exactly these questions in a natural conversation, without anyone having to search through long help pages.

A conversation in the user’s own language

Udai speaks and understands 11 languages: Hindi, Tamil, Bengali, Telugu, Kannada, Malayalam, Marathi, Gujarati, Punjabi, Odia, and English. A user simply asks a question. Udai listens, works out the answer, and replies in the same language, with natural speech, matching lip movements and expressive hand gestures.

What sets Udai apart is how it is built. AI avatars rely on expensive, specialised graphics hardware to bring a face to life. Udai takes a simpler route. The character is created from pre-filmed footage, and its lip movements are matched to its speech in real time using lightweight processing that runs in a web browser.

The result is a smooth experience at 24 frames per second on ordinary servers, at a fraction of the usual cost per user. For a programme that serves hundreds of millions of people, that efficiency is what turns a nationwide rollout from an ambition into a practical plan.

“Our focus with Udai was to make Aadhaar-related information easier to access through natural conversation. Combining multilingual voice interaction with official reference content allowed our team to build an experience that is practical, approachable, and useful to users,” said Yogesh Agarwal, Founder and CEO, Daffodil Software.

Answers drawn only from official sources

The assistant uses official UIDAI material as its reference knowledge base: frequently asked questions, provisions of the Aadhaar Act, and government policy documents on Aadhaar services. It covers the topics users ask about most:

Enrolment and registrationAddress and demographic updatesFees, required documents and eligibilityeKYC and Virtual IDLinking Aadhaar with bank accounts, PAN and mobile numbersmAadhaar servicesGrievance redressal

Users don’t need to phrase their questions in any particular way. Udai understands everyday language, whether a question is spoken in English, Hindi, or asked in a mix of both, and finds the most relevant official information to answer it.

Built to be accurate, respectful, and secure

When a public service speaks directly to users, trust matters as much as convenience. Udai is protected by three layers of safeguards.

Accuracy first. Udai answers only from its verified knowledge base. Responses are grounded in a curated knowledge base of official UIDAI material. If a question falls outside Aadhaar, it guides the user back rather than offering an answer it cannot stand behind.

Respectful conversations. A screening layer catches abusive or offensive language in English, Hindi, and Hinglish before it reaches the assistant. Screening is designed to identify abusive language while supporting legitimate queries

Protection against misuse. Udai cannot be talked into abandoning its role, pretending to be someone else, revealing its internal setup, or answering beyond its approved scope. These checks work almost instantly, so users experience no delay.

What comes next?

Udai is planned to roll out in two phases.

In the first phase, the mascot will be placed in Aadhaar Centres. Visitors will be able to check information and understand processes on their own, such as which documents they need for an address change. This frees centre staff to focus on their core work instead of answering the same questions again and again.

In the second phase, Udai will come to the Aadhaar website and mobile app, taking the place of the current text-based chatbot, which was also built by Daffodil.

About Daffodil Software

Daffodil Software is a software engineering and AI solutions company serving businesses across industries. Its services span software consulting, product engineering, UI/UX design, AI/ML development, quality assurance, cloud and DevOps, and maintenance. The company serves sectors including healthcare, fintech, banking, technology, and digital commerce. Its client portfolio includes organizations such as the Reserve Bank of India, Mount Sinai Hospital, Maruti, Samsung, Pramerica Insurance, and Dangote Group. Daffodil Software has also been featured in industry research and recognition by Gartner, Everest Group, Zinnov, and Frost & Sullivan. For more information, visit https://www.daffodilsw.com

Media contact

Kunwar Pal Singh
media-relations@daffodilsw.com

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