Results

Quantum computing pure plays duel with giants, rivals

Quantum computing's pure plays have bulked up balance sheets and continue to bet they can upend larger rivals backed by big corporations including Alphabet, IBM and Honeywell.

In recent weeks, Google, IBM and Quantinuum have outlined roadmaps and quantum computing milestones. Meanwhile, the pure play quantum companies have surged on Wall Street (and given a big chunk of those gains back) with more going public. For instance, Infleqtion, which is focused on neutral atom architecture, will go public via a merger with special purpose acquisition company Churchill Capital Corp X.

The results from the quantum computing pure plays land after Google outlined advances in its Willow processor and Quantinuum launched its next-gen Helios system. Toss in IBM's quantum computing efforts and it's pretty clear that the pure plays in quantum computing are Davids trying to slay Goliath (or a series of them). Those aforementioned giants are all focused on superconductors to drive quantum systems.

Rigetti is also aligned with superconducting, but D-Wave is focused on annealing and IonQ plays in the trapped ion space. Simply put, there's a VHS-Betamax moment ahead, but it remains to be seen how long until a clear winner is declared.

What is clear is that the pure play quantum providers have floated shares to raise capital. IonQ has $1.5 billion in cash and equivalents as of Sept. 30 and $3.5 billion following a $2 billion equity offering in October. D-Wave had a cash balance of $836.2 million and Rigetti checked in with $600 million in cash and equivalents. In other words, there's enough funding to surf the quantum computing technology shifts.

Nevertheless, it's also clear the market is immature. Rigetti reported third quarter revenue of $1.9 million. D-Wave had third quarter sales of $3.7 million. IonQ, the largest of the publicly traded pure plays in quantum, had third quarter revenue of $39.9 million and projected more than $100 million in revenue. IonQ has bulked up via acquisitions and aims to offer an integrated stack of quantum compute, networking, sensing and security.

Constellation Research analyst Holger Mueller said:

"The quantum space is in an interesting phase, as we see both the giants and the Davids. The interesting thing is that the Davids often are older than the giants, so they have adapted to the new competitive landscape and state of quantum. Usually though we should see a new generation of Davids pop up - but it looks like the hardware window is closed for now. Davids will likely show up on the algorithm and software side. A further challenge to first generation Davids is quantum advantage will be achieved by a combination of AI / HPC and quantum. Smaller quantum players will  need to partner for the former two. The good news is that there are "Ggiants" in HPC that do not have a quantum play (like HPE) and AI (like Nvidia) that will be eager to partner.  The biggest challenge: CxOs cannot pick the winners for their initial quantum workloads yet - but it is getting closer and closer to make that call."

Here's what you need to know about the latest round of quantum computing results.

IonQ (trapped ion)

IonQ CEO Niccolo de Masi said the third quarter was transformative because it saw a "tremendous symphony of technical progress, talent attraction and successful expansion of our vision to lead globally in the business of quantum."

de Masi's take aligned with what he said on IonQ's investor day. The big picture: IonQ is the leader in quantum computing and will become the next Nvidia.

IonQ's #AQ 64 Tempo system launched ahead of schedule and de Masi is focused on use cases that deliver value today. IonQ is also betting heavily on quantum networking.

"IonQ has a truly unique ability to land and expand quantum computing, quantum networking, quantum sensing and quantum cybersecurity. Our strategy is to expand our technical lead in each quantum product family and connect our products together to provide unique solutions to allied sovereigns and major multinationals alike," said de Masi, who noted IonQ has more than 1,100 patents pending and granted.

de Masi also touted 99.99% fidelity for 2-qubit gates. IonQ is also taking aim at incumbents focused on superconducting as the company has outlined use cases with Ansys for engineering and AstraZeneca for drug discovery. "Our newest system, which we unveiled at our Analyst Day on September 12 is called Tempo. Public benchmarks show Tempo has a compute space 36 quadrillion times larger than the leading commercial superconducting system in the market. We are proud that Tempo is scheduled to ship in 2026 and has a computational space approximately 260 million times larger than our current fully commercialized Forte system," said de Masi.

The IonQ CEO added:

"While numerous companies, public and private, have added the word quantum to their corporate name for decades, we can confidently state that in almost every case beyond IonQ, this is just a branding attempt. Terms like quantum-inspired, quantum annealing or analog quantum simulators all represent toy machines compared to the real deal, which is universal fully entangled gate-based quantum computing."

Things to know:

  • IonQ is targeting 1,600 logical qubits in 2028 and 80,000 in 2030.
  • For 2025, IonQ is projecting revenue of $106 million to $110 million.
  • The company reported a third quarter net loss of $1.1 billion on revenue of $39.9 million, up 37% from a year ago.
  • IonQ advanced to Stage B of DARPA's Quantum Benchmarking Initiative (QBI).
  • IonQ is available on AWS Braket, Microsoft Azure, and Google Cloud Platform.

Rigetti Computing (superconducting)

Rigetti Computing reported a third quarter net loss of $201 million on revenue of $1.9 million and had $600 million in cash and equivalents as of Nov. 6.

Dr. Subodh Kulkarni, Rigetti CEO, said the company will deliver its chiplet-based quantum system with more than 100 qubits by the end of 2025. The system has a 99.5% median two-qubit gate fidelity.

Rigetti is aiming for a quantum system with more than 150 qubits by the end of 2026 with a 99.7% median two-qubit gate fidelity and top 1,000 qubits by the end of 2027 with a media two-qubit gate fidelity of 99.8%.

The company stands out in the pure play quantum space since it has decidedly less bravado. Kulkarni said quantum computing is a challenging space and the company plans to grow organically even though it has enough cash to make acquisitions.

Rigetti Computing CEO: Quantum advantage 4 years away

"For quantum advantage, we still think we need a 99.9% 2-qubit gate fidelity, as well as some form of error correction. So between '27 and '29, which is when we still believe we accomplish quantum advantage, is getting the fidelity to that 99.9% and also error correction up," said Kulkarni.

Rigetti said it sold two quantum systems for $5.7 million for two 9-qubit Novera systems, which can be upgraded to increase the qubit count. The systems will be delivered in the first half of 2026 to an Asian technology manufacturing company and an applied physics and AI startup in California.

Kulkarni said the two systems include everything from the dilution refrigerator to control systems. The complete systems can be upgraded to and drive additional revenue.

Things to know:

  • The company has a 3-year $5.8 million contract from the Air Force Research Laboratory to advance superconducting quantum computer networking with QphoX, a Dutch quantum startup.
  • Rigetti wasn't selected for Stage B of DARPA's QBI, but received constructive input. The company said it is optimistic that it will be chosen for Stage B in the coming months.
  • DARPA's feedback for Rigetti revolved around error corrections and some areas of long-rang coupling.

Rigetti sees a big opportunity for hybrid supercomputing that bridges high performance computing and quantum as well as Nvidia's NVQLink effort. "We believe superconducting quantum computing is most amenable for hybrid computing compared to other modalities which are 1,000 times slower, like trapped ion or pure atom modalities," said Kulkarni.

Kulkarni said the company was feeling good about the roadmap, its ability to execute and a partnership with Quanta Computer to build systems.

D-Wave (annealing)

D-Wave reported third quarter revenue of $3.7 million, up 100% from a year ago, with a net loss of $140 million. The net loss includes a non-cash charge due to the company's warrants. The company has $836.2 million in cash and equivalents.

The company, which is focused on the annealing approach to quantum computing, recently launched its Advantage2 system. Quantum annealing is designed for optimization and probabilistic sampling problems in areas like logistics, finance and machine learning. This specialized approach isn't general purpose.

CEO Alan Baratz said on the company's earnings call:

"As other quantum companies remain in R&D mode, we are laser-focused on a path to profitability built on customer value. We signed a number of new and renewing customer engagements in the third quarter for both commercial and research applications. These engagements include one of the largest U.S.-based international airlines, SkyWater, the nation's largest pure-play semiconductor foundry. Japan Tobacco's Pharmaceutical division, which is exploring new Quantum AI applications in drug discovery, Yapi Kredi, one of the leading banks in Turkey and Korea Quantum Computing, a company specializing in quantum computing R&D, quantum security solutions and AI infrastructure in Korea."

Baratz's added that D-Wave is focusing on hybrid workloads with supercomputers. Baratz said the company's approach is to deliver value today with optionality in the future based on whatever quantum computing approach wins. Baratz said D-Wave is using superconducting gates for its annealing and emphasized the point.

On D-Wave's second quarter and first quarter earnings calls, Baratz didn't go into details about how much aligned it was with superconducting. It's possible that D-Wave's cryogenic control system it uses for its annealing would be critical to any superconducting gate model quantum company.

The D-Wave CEO said, "we believe that one will clearly emerge victorious in the long run and that approach is superconducting." Baratz, who said ion trap and neutral atom approaches have some advantages today, also took aim at IonQ's investor pitch.

"We recently heard an ion trap company spent hours discussing their technology advantages at an analyst event, but not once did they mention gate speed. With a potential performance disadvantage of up to 10,000x, I can see why they might have forgotten to discuss that key metric," said Baratz.

Much of Baratz's time on D-Wave's most recent earnings call was defending its annealing approach. "We recently had a fair amount of chest pounding from quantum leaders. Let me be clear. Anyone who characterizes quantum annealing as not real quantum is either intellectually incapable of understanding the physics and science or has chosen to put their head in the sand because they are worried about the competitive threat," said Baratz.

D-Wave's Advantage2 quantum computer generally available

Things to know:

  • D-Wave has more than 100 revenue-generating customers over the last four quarters.
  • For the nine months ended Sept. 30, D-Wave had revenue of $21.8 million. Of that total, $4.2 million was quantum computing as a service (QCaaS) and $2.1 million was professional services.
  • The company has 100 QCaaS customers and 48% of them are commercial. D-Wave offers its systems through its Leap cloud service.
  • D-Wave's business strategy is to focus on commercial customers not government funded R&D.
  • Baratz said the company is "laser-focused on quantum computing" not ancillary revenue streams like networking, sensing and quantum key distribution.
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Anthropic: Claude eyes real world impact, industrial use cases

Anthropic is looking to infuse its Claude models into industrial use cases, but those real world applications carry more risk and require domain expertise.

Speaking at the IFS Industrial X Unleashed conference in New York, Anthropic's Garvin Doyle, Applied AI Lead, said it's one thing to apply AI to industries like financial services and software development but another game entirely in real world settings.

"The Anthropic vision is to facilitate the safe transfer of AI across the economy," said Doyle. "The risk is elevated when you bring AI into the real world, into the factories, plants and field operations."

Doyle was on stage with Kriti Sharma, CEO at IFS Nexus Black, talking about industrial AI. IFS Nexus Black, a team of forward deployed engineers, has partnered with Anthropic and used its Claude models to launch Resolve, a system for industrial AI use cases.

"Building for the real world is fundamentally different," said Sharma.

IFS and Anthropic announced a broad partnership focused on taking Claude to industrial AI use cases. William Grant & Sons, the distillers behind Grant's whisky and Hendrick's gin, is a flagship customer of IFS Nexus Black and Anthropic via Resolve. The distillery has used Resolve to predict failures before they happen and estimates that it will save £8.4 million annually at one site.

Doyle said AI today has largely stuck to the digital domain since it's easier to simulate behaviors. "When you translate to the real world there are a lot of problems and challenges that we just haven't traversed yet," said Doyle. "Getting information in the real world requires working through SCADA systems, looking at diagrams and interacting with subject matter experts with institutional knowledge that hasn't been codified in a digital system."

As a result, industrial AI requires information, actions and prerequisite behaviors before data is incorporated into a model, explained Doyle. Once that expertise is incorporated into a model, improvements can scale in heavy industries like other sectors.

Doyle said incorporating AI into the real world will drive real business value. "A lot of the conversation today has been grounded in not building solutions but in adding as many AI buzzwords as possible," he said. "Real business outcomes are not just about technology. It's the evaluations, the subject matter expertise and the feedback loop to the underlying technology and the interface layer that connects them. One aspect doesn't drive a solution. It's the cohesion of all of the aspects."

Other key points from Doyle:

  • "Fundamentally, Anthropic is an enterprise AI company," he said. "Competitors are very excited about consumer features but we focus squarely on the enterprise and what that entails. We can't create systems that are so constrained they are only step by step workflows that negates AI benefits, but we need to have some guardrails so these things can operate." See: OpenAI, Anthropic increasingly diverge as strategies evolve
  • AI hit an inflection point in March of 2025 due to reasoning capabilities in models. Today models are constrained to narrow tasks, but will be combined with subject matter expertise for broader reach. "As we extend codified training examples for economically valuable tasks, the model is going to get pervasively better at everything outside of the digital domain too," said Doyle.
  • "There's so much opportunity in the field and what we can do radically different," he said.

 

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QAD | Redzone aims to fuse AI, process intelligence to reinvent manufacturing

QAD | Redzone is looking to infuse AI, process intelligence and frontline worker empowerment as it looks be the ERP provider of choice for mid-market manufacturing companies. The goal: Provide the systems that reinvent manufacturing.

The company launched its next generation ERP platform, QAD Adaptive powered by Champion AI, an agentic AI engine that's designed to turn manufacturing systems of record and make them actionable. Those efforts complement Redzone Connected Workforce, which aims to bring process intelligence to frontline workers for better decision-making.

QAD | Redzone's Champion AI is powered by Amazon Web Services and its Amazon Bedrock AgentCore and Amazon SageMaker. As part of the AWS partnership, QAD | Redzone will transition its global IT workloads and internal platforms to AWS. For AWS, the QAD partnership is handy given its push into manufacturing and industrial AI use cases.

AWS CEO Matt Garman said in a statement that the QAD | Redzone partnership is about "moving agentic AI from proof of concept to production" to "incorporate your unique data into workflows."

For QAD | Redzone, the launches are designed to capitalize on a renaissance in manufacturing and the intersection of AI and industrial use cases. The company announced the news at its Champions of Manufacturing event in Dallas.

Sanjay Brahmawar, CEO of QAD | Redzone, said the company is looking to power the next-generation of manufacturing companies that'll be more AI-powered, data driven and nimble. "Manufacturers who lead the next generation of manufacturing will be those that are the most adaptive: turning speed into strategy, data into decisions, and people into catalysts of change. This isn’t just a better version of ERP, it's a new model altogether," said Brahmawar.

Release highlights include:

  • Champion AI Agentic Platform, which includes AI agents focused on implementation, productivity and business optimization. The agents are designed to reduce implantation time and deliver value faster.
  • A fully embedded Warehouse Management System and enhanced Production Scheduling Model.
  • Champion Pace Rapid Implementation, which is designed to streamline and automate implementation tasks.
  • Industry-focused enhancements including features for complex manufacturing environments and Unique Device Identification labeling tools to improve supply chain efficiency.
  • QAD | Redzone said it has acquired Kavida.ai in a move that will bring AI agents to its procurement and supply chain workflows.

Brahmawar acknowledged that speed to decisions is going to be a critical battleground going forward. The companies that are able to use AI to optimize processes and automate to deliver value quickly will win.

Indeed, Constellation Research analyst Mike Ni said in a recent report that decision velocity will separate winning enterprises from also rans. For manufacturers, which have to deal with tariffs, supply chain shocks and economic volatility, taking data to decision in real-time is everything. "Enterprises have spent billions on data, analytics, and artificial intelligence (AI). The bottleneck and industry focus are no longer technology but decision-making," said Ni in a report. "Decision velocity, defined by how fast and effectively an organization can sense, decide, act, and learn to lift measurable outcomes quickly and accurately is the new yardstick by which boards and CFOs judge AI investments as enterprises move from proofs of concept (POCs) to funded AI initiatives."

A look at the strategy

Brahmawar joined the company in March after serving as CEO of Software AG. In a briefing, Brahmawar walked through the QAD | Redzone strategy. Among the key points:

The manufacturing opportunity. Brahmawar is a manufacturing geek and started his career on a Honda shop floor assembling engines. "QAD was born because the traditional ERP vendors were focused on the wide enterprise," he explained. "They didn't have the depth and attention to everything that happens on the manufacturing shop floor starting from the bill of materials."

QAD | Redzone targets manufacturers with annual revenue between $200 million and $5 billion. In many ways, Brahmawar is bringing QAD back to its manufacturing roots with an ambition to be the best ERP provider for the sector. "I don't want to be everything to everybody. I want to be the best in manufacturing," he said.

Brahmawar said manufacturing is having a watershed moment as governments, countries and multiple geographies see the sector as strategic for national security, economic growth and job creation. QAD's customer base is focused on automotive, food and beverage and discrete manufacturing.

However, there's also a paradox with manufacturing. Capital is flowing into manufacturing and there's not enough capacity as well as an aging workforce. Automation and robotics is capital intensive and rigid. "You can have more productivity and more effectiveness through agentic layers, agentic systems and AI," said Brahmawar. "QAD can create more productivity and also create systems of action that will attract talent to manufacturing."

QAD | Redzone product pillars. Brahmawar said the first pillar for QAD | Redzone is Redzone, which is the company's system for front line workers. "We bring information and data right into the hands of frontline workers," said Brahmawar. The other pillar for QAD is adaptive with an intelligent backbone that's based on process intelligence. And the last pillar is Champion AI, which is AI tools for the manufacturing workforce to increase capacity.

Here's a look at some of the moving parts behind QAD's product pillars and how they play into the manufacturing renaissance.

The data play. Amit Sharma, President of Manufacturing ERP at QAD | Redzone, said one thing to watch in manufacturing is the data behind the value chain with retail, manufacturing and distribution. "The information you have on demand, capacity, planning and availability is going to be much more valuable than the software," said Sharma. "You just need the software to participate.

QAD | Redzone's Champion AI is designed to connect to various data stores, including SAP. Sharma said Champion AI is informed by process intelligence that tells you how your processes are executing today and how they can be improved.

Process intelligence is built into QAD's systems. "Our plan with our ERP is that everything is in one system and providing the intelligence to achieve your KPIs. We have the tools and the means to automate actions with human ability," said Sharma. "That's the vision we are driving toward."

Enabling the frontline manufacturing worker. Ken Fisher, President of Redzone, said QAD's goal with Redzone is to "transform manufacturing by empowering the frontline." According to Fisher, manufacturers that are adaptive will win. Frontline workers are the ones in manufacturing that make the calls. "We provide culture change at scale where operators have ownership. They know what their targets are and what their losses are and they're empowered to do something about it," said Fisher. What Redzone does is connect engineers honing processes directly to the front lines to speed up corrective actions with a data feedback loop tied into the ERP system.

Going forward it's worth watching how QAD | Redzone develops. Manufacturing is the belle of the AI ball and is strategically significant to various countries and regions looking to control their industrial destinies. Simply put, the time to fuse AI, process intelligence and manufacturing systems is now. "For manufacturers, the biggest risk is inaction," said Brahmawar.

Constellation Research analyst Holger Mueller said:

"AI is coming to the shop floor and is likely the biggest transformation of the hand to machine ratio since the introduction of the steam engine. It's good to see that QAD is thinking about the frontline worker in the factory, and providing the platform for the future of work on the shop floor, as enterprises transition from human only to hybrid and likely sooner than later to robot-only shop floors." 
 

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IFS teams up with Anthropic, Siemens, Boston Dynamics, 1X, showcases industrial AI use cases

IFS CEO Mark Moffat said industries need to embed AI into physical operations in manufacturing, utilities, defense systems and supply chains to better compete globally and become autonomous. IFS launched new AI-powered products as well as partnerships with Anthropic, Siemens, Boston Dynamics and 1X Technologies. 

Speaking at IFS' Industrial X Unleased conference in New York, Moffat outlined a vision of Industrial AI -- Applied. "We're at a fork in the road," said Moffat. "This isn't a tech cycle. It's a fundamental choice about whether AI becomes the backbone of the industries that power our world or remains a toy."

Moffat said the $10 trillion flowing into industrial infrastructure and assets is a positive, but there's a gap because little of those funds are going into applying knowhow about running a factory, fixing a turbine or preventing a wildfire. Moffat said IFS is looking to be the control layer that connects industry infrastructure and AI.

"Generic AI misses the context and deep understanding of the physical world," said Moffat, who laid out the IFS strategy combining AI, enterprise applications and processes and industrial use cases.

Moffat said:

"We're moving from demos and brochures and marketing into as my son would call it, IRL, in real life, in the real world. AI that can orchestrate physical operations and supply chains and plants in real time, AI that can unleash a new 10x capacity from the workforce."

The IFS CEO said that investment into AI is staggering, but there's a big gap. "There's a gap between the application of financial capital into the practical, real world AI going into factories, fixing turbines and preventing wildfires. We've focused on the practical application of this technology and bringing it into the real world," said Moffat.

Building an industrial AI ecosytem

IFS' approach is to orchestrate robotic workers, designed for dangerous jobs, human experts, and digital AI workers as one integrated system. To reach this goal, IFS is teaming up with the likes of Anthropic, Siemens and Boston Dynamics and layering AI throughout its enterprise software platform that includes enterprise resource planning, asset management, field service applications and energy and resources software.

At its Industrial X Unleashed conference in New York, the company announced the following:

An Anthropic strategic partnership that will bring Claude models to industrial applications with tooling for specific use cases. For instance, IFS and Anthropic unveiled a voice-first offline AI for frontline technicians working in extreme conditions. According to IFS, 70% of the industrial workforce works in areas where connectivity in spotty.

IFS said its Anthropic partnership revolves around its IFS Nexus Black unit and its IFS Nexus Black Industrial AI applications, which are powered by Claude models. Key items include:

  • The partnership combines the expertise of IFS Nexus Black, a team that adapts AI to industrial AI specific use cases, and Claude models.
  • IFS launched Resolve, which gives technicians and field workers to Claude trained on use cases in aerospace and defense, construction and engineering, manufacturing, energy and utilities.
  • Resolve will help frontline workers predict and prevent faults faster with multi-modal data, connect technicians to the right parts with optimized scheduling and streamline workflows.
  • IFS is looking to use AI to address industries dealing with aging infrastructure as well as expertise.
  • William Grant & Son, the distiller behind Grant's whisky and Hendrick's gin, used Resolve to cut downtime and revamp operations.

IFS outlined a partnership with Siemens Grid Software to use IFS as part of its intelligent grid infrastructure updates. Siemens and IFS said they will combine Siemens' grid planning, electrification and smart infrastructure applications with IFS's enterprise asset management, field service management and AI scheduling optimization software.

Key items include:

  • IFS software will be integrated into Siemens Gridscale X applications.
  • The goal is to provide a platform that will create a path to an autonomous, self-optimizing grid operations stack.
  • The integration will be modular and designed to be deployed without rip-and-replace projects.

Boston Dynamics, IFS and 1X Technologies said they will collaborate to integrate robotic and humanoids into industrial workflows. The partnership with Boston Dynamics combines the robotics company's autonomous inspection robots with IFS.ai to enable decision-making in the field. According to the companies, the Boston Dynamics and IFS collaboration can address labor and skills shortages for industrial customers.

Key items include:

  • The companies showcased a Boston Dynamics Spot robot doing inspection and feeding multimodal data to IFS.ai for analysis and decision-making.
  • IFS.ai takes that data and triggers workflows in the field.
  • The collaboration focuses on field operations in manufacturing, energy, utilities, mining and other asset-intensive sectors.
  • Use cases include autonomous inspections to reduce human exposure to hazardous environments, efficiency for faster response times, and uptime improvements.

Under the 1X Technologies partnership, IFS and 1X will collaborate to combine humanoid robots with IFS.ai. The companies said they will develop and deploy production-ready robotics packages for manufacturing, utilities, aviation and other industries. Here's a look at the 1X-IFS plan:

  • IFS and 1X will aim to create a unified digital-physical operational environment that combines robotics and enterprise business processes.
  • The two companies will work with customers to industrial and validate humanoid robot use cases including factory automation, IoT powered operational data collection and field service and maintenance.
  • IFS and 1X said that integrated offerings will be commercially available in 2026.

IFS saw its annual recurring revenue surge 22% from a year ago with cloud revenue growth of 31%. The company's industrial AI stack includes IFS.ai, which is designed to embed industry-specific intelligence across its applications, Nexus Black, an AI innovation accelerator, and IFS Loops, a portfolio of agentic digital workers.

The company also acquired 7Bridges in the third quarter for AI-powered supply chain, logistics and transportation optimization tools as well as TheLoops, an AI workforce provider.

In October, IFS outlined 10 digital workers with 50 agentic AI skills as it builds to a roadmap of 100 skills that will be embedded into manufacturing, energy, utilities, telecom, construction, aerospace and defense and service industries. IFS Loops Digital Workers are designed to manage complex workflows and make decisions that continually optimize processes.

The big picture

Here's a look at the high-level takeaways from IFS' conference in New York.

  • Moffat's take is that AI can retool industrial infrastructure while maintaining jobs. Manufacturing already faces sever worker shortages.
  • According to Moffat, there are multiple trends pointing to the power of AI and industries including aging industrial infrastructure, labor shortages and retiring expertise and the need for automation and faster decision-making. IFS’ core industries include aerospace and defense, energy utilities, construction and engineering, manufacturing and telecommunications.
  • IFS is emphasizing industrial AI and that approach can stand out in a stagnant ERP space.
  • The company is also highlighting real-world deployments throughout its conference and showing real business impact. IFS is showcasing blue-collar AI and how new technology can empower frontline workers.
  • IFS is focused on building ecosystem alliances that can bridge the digital and physical worlds. These partnerships include Microsoft, Nvidia, Siemens, Anthropic and Boston Dynamics to name a few.
  • The company is looking to productize its AI applications rather than build custom-built systems, but will use forward deployed engineers to speed up deployments.
  • Mohamed Kande, Global Chairman at PwC, said industrial AI will be required to get returns from the $1.7 trillion invested in AI infrastructure. "Do you deploy today the old way, or do you use industrial AI to power all that infrastructure? Imagine being a company investing all of this money and you build something that doesn't have the right artificial intelligence in it. What happens in three or five years?" said Kande, who said boards of directors and CEOs are increasingly comfortable with placing big AI bets. 

Constellation Research's take

Constellation Research CEO R "Ray" Wang said:

"While frontier AI models and infrastructure platforms grab headlines, the critical missing piece has been the orchestration layer, the industrial operating system that embeds AI directly into mission-critical workflows. Customers seek deep domain expertise from their trusted AI partners, especially in manufacturing, utilities, aerospace, and energy. The AI Age isn’t about adding AI features to legacy software. It’s about architecting the control plane for the next generation of intelligent industrial operations where autonomous execution happens at scale, in real-time and achieving decision velocity for tangible business outcomes."

Constellation Research analyst Holger Mueller said:

"AI is changing everything and with physical AI and robotics it changes the manufacturing process. Vendors like IFS need to cater to a mix mode shop floor where humans and robots work together with the common goal of delivering projects at high quality and on time. Laying the groundwork for the agentic / robotic factory is a key step for enterprises that like will happen sooner than later."

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Cisco delivers strong Q1, starts to capture AI infrastructure spend

Cisco reported better-than-expected first quarter results, raised its outlook and said it landed more AI infrastructure orders from hyperscalers and posted strong networking growth.

The company reported first quarter net income of $2.9 billion, or 72 cents a share, on revenue of $14.9 billion, up 8% from a year ago. Non-GAAP earnings for the first quarter were $1 a share.

Wall Street analysts were expecting Cisco to report non-GAAP fiscal first quarter earnings of 98 cents a share on revenue of $14.78 billion.

CEO Chuck Robbins said Cisco saw "widespread demand for our technologies."

Mark Patterson, Cisco CFO, said that the company's "relevance in AI continues to build and we have a multi-year, multi-billion-dollar campus refresh opportunity starting to ramp, with strong demand for our refreshed networking products."

By division, Cisco said its first quarter networking revenue was up 15% with observability up 6%. Security and collaboration were down 2% and 3% from a year ago, respectively. Security revenue was hampered by Splunk, which saw more customers opt for cloud deployments. That mix shift affected results this quarter, but is a long-term benefit for Cisco.

As for the outlook, Cisco projected second quarter revenue of $15 billion to $15.2 billion with non-GAAP earnings of $1.01 to $1.03 a share. For fiscal 2026, Cisco projected non-GAAP earnings of $4.08 a share to $4.14 a share on revenue of $60.2 billion to $61 billion.

Key points from Cisco executives from the earnings call:

  • Robbins said, "we see a solid pipeline through the rest of the year." He said Cisco is seeing strong demand for routers, optical networking and switches. "We are beginning to see inferencing use cases where we are winning there," said Robbins. Four hyperscalers inked big deals with Cisco, which is also landing neo-cloud providers.
  • "We expect Cisco's AI opportunity across sovereign neo-cloud and enterprise customers to ramp in the second half of fiscal year '26," said Robbins.
  • The upside in AI infrastructure from enterprises should continue, said Robbins. "We know many customers still have a lot of work to do to ensure they have the modern, scalable, secure networking when they're supporting their AI goals," said Robbins.
  • "We're also seeing consistent progress across our industrial IoT portfolio, including new ruggedized equipment, with orders growing more than 25% year over year. In Q1 infrastructure, we expect this demand to increase, driven by onshoring of manufacturing to the United States, the increase of AI workloads at the network edge and the emergence of physical AI infrastructure orders," said Robbins.

 

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Anthropic to spend $50 billion on AI infrastructure via Fluidstack partnership

Anthropic said it will invest $50 billion in building its own AI data centers in a partnership with Fluidstack. The first data centers will be built in New York and Texas with more sites on deck.

The move comes after Anthropic announced it would use Google Cloud TPUs as well as AWS Trainium2 supercluster. Anthropic also uses Nvidia processors. The multi-cloud and multi-GPU approach was differentiated relative to OpenAI's spending spree on operating its own data center. Now Anthropic has decided that it has to roll its own AI infrastructure too.

According to Anthropic, the Fluidstack partnership will focus on custom-built infrastructure designed for the large language model provider's workloads and R&D.

Like most announcements covering AI infrastructure, Anthropic was sure to mention the project will create 800 permanent jobs and 2,400 construction jobs and play into US AI leadership. The data centers will power up throughout 2026.

Dario Amodei, CEO of Anthropic, said the company is getting closer to AI that can accelerate scientific discovery and solve complex problems. "These sites will help us build more capable AI systems that can drive those breakthroughs," he said.

For Fluidstack, the deal with Anthropic is a big win. Fluidstack counts Meta, Nvidia, Samsung, Dell, Honeywell and others as core customers.

Holger Mueller, an analyst at Constellation Research, said: "Clearly, Anthropic is charting a different course compared to OpenAI - the question is - what is the price for the flexibility? That is - how much does the portability need for Anthropic.  Hopefully it's not only a cost arbitration game."

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IBM launches IBM Quantum Nighthawk processor

IBM launched its most advanced quantum processor, IBM Quantum Nighthawk, and announced its IBM Quantum Loom, an experimental processor that demonstrates all of the processor components for fault-tolerant quantum computing.

Big Blue announced the roadmap additions at its annual quantum developer forum.

The news from IBM lands as Quantinuum launched its Helios system and Google highlighted its advances. In addition, pure play quantum computing companies have been able to build up their balance sheets as they develop systems.

For IBM, the goal is to deliver quantum advantage by the end of 2026 and fault-tolerant quantum computing by 2029. IBM has offered frequent updates about its quantum computing roadmap with two in 2025.

Here's a look at the key announcements from IBM.

IBM Quantum Nighthawk is designed to complement the company's quantum computing software stack and architecture to deliver quantum advantage. IBM Quantum Nighthawk will be delivered by the end of 2025.

Key points:

  • The quantum processor will be 120 qubits linked together with 218 tunable couplers. Nighthawk will have more than 20% more couplers compared to IBM Quantum Heron.
  • Nighthawk will be able to execute circuits with 30% more complexity than Heron with low error rates.
  • IBM's latest architecture gives users the ability to explore more demanding problems that require up to 5,000 two-qubits gates.
  • By the end of 2026, IBM said IBM Quantum Nighthawk will deliver up to 7,500 gates and up to 10,000 gates in 2027.
  • By 2028, Nighthawk systems could support up to 15,000 two-qubit gates with more than 1,000 connected qubits extended through long-range couplers.

Quantum advantage will be reached by the end of 2026 and be verified by the broader ecosystem. IBM contributed three experiments for quantum advantage to be verified by the broader ecosystem.

Qiskit, IBM's quantum computing software, will get a new execution model to enable fine grain control and a C-API for HPC-accelerated error mitigation.

IBM will deliver a C++ interface to Qiskit to help developers bridge HPC and quantum computing. By 2027, IBM noted that it will extend Qiskit with computational libraries for machine learning and optimization.

The company also said that it will move toward a large-scale fault-tolerant quantum computer by 2029. The effort will be led by IBM Quantum Loon, an experimental processor. Key items for IBM Quantum Loon:

  • Loon has a new architecture to implement and scale components for high-efficiency quantum error correction.
  • IBM has proven it is possible to use classical computing hardware to accurately decode errors in real-time (less than 480 nanoseconds) using qLDPC codes. That ability will be coupled with Loom to scale high-fidelity superconducting qubits.

The company said that it will scale its 300mm quantum wafer fabrication in the Albany NanoTech Complex in New York. The lab will be used to expand its quantum processor development and wafer manufacturing.

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AMD sees big growth over next 3 to 5 years, AI boom continuing

AMD projected compound annual revenue growth rates of 35% over the next three- to five years and said demand for AI infrastructure and its chip portfolio is strong.

CEO Lisa Su said during AMD's investor day that the pace of AI infrastructure spending and pace of change is higher than she's ever seen before. "We see a tremendous opportunity ahead to deliver sustainable, industry-leading growth," said Su.

Su in a question and answer session noted that that compound annual growth rate may be front loaded over the three- to five-year time horizon. "We're giving a three to five year TAM and the outer years have a little bit less visibility than the near term years," said Su. "We would expect the near term years to grow faster than 80%."

AMD is seeing strong interest in its AI accelerators. "There is a desire for significant amount of compute. We are working with the supply chain today to make sure that we have the broad ability to support all the compute that's required," said Su.

Here's a look at long-term growth targets over the next three to five years.

  • AMD sees non-GAAP earnings topping $20 a share with non-GAAP operating margins of more than 35%.
  • AMD's data center business will grow at a 60% compound annual growth (CAGR) rate with 10% for its PC and gaming and embedded units.
  • The company sees its EPYC CPU server chip portfolio gaining more than 50% market share. In data center AI, AMD sees CAGR of more than 80%.
  • PC market share will top 40%.

On the product front, AMD executives outlined the AMD Instinct roadmap including Helios systems with AMD Instinct MI450 Series GPUs followed by the MI500 in 2027.

The company also touted its next-gen Venice CPUs and AI networking offering for scale-up and scale-out workloads.

Su was asked about the risk to AI infrastructure spending, notably how much of it has to be funded by OpenAI. Su said AMD "is quite disciplined how we plan these things" and that the company is "comfortable that we know how to do it."

She added that the companies that are funding AI infrastructure such as Google, Microsoft and AWS are well funded. There's also sovereign nations spending heavily. Su said:

"All of the other large hyperscalers who are talking about raising their forecasts are extremely well funded. Their balance sheets are really strong, and the fact that they are choosing to invest more in AI should be a good indicator to the audience that they see value in it."

Regarding OpenAI, AMD's Su said:

"The reason that we are so forward leaning on this is it is great for us in terms of just the amount of learning that we get from engaging at gigawatt scale with a customer that's on the bleeding edge of foundational models. We're doing this in a very structured way. This is a very unique moment in AI and we shouldn't be short sighted. If the AI usage grows as much as we expect there's going to be plenty of financing."

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QAD | Redzone acquires Kavida.ai to add procurement AI agents

QAD | Redzone said it has acquired Kavida.ai in a move that will bring AI agents to its procurement and supply chain workflows.

Terms of the deal weren't disclosed.

For QAD | Redzone, the Kavida.ai purchase will accelerate its Champion AI roadmap. Kavida.ai's knowhow in procurement agent training and inbox-to-ERP automation will be integrated into the company's portfolio. QAD | Redzone consists of three core interconnected offerings:

  • QAD, an ERP system focused on midmarket manufacturers.
  • Champion AI, a set of AI tools that works across the platform to enable the manufacturing workforce.
  • Redzone, a system to bring data, AI and automation tools for frontline workers to speed up decisions.

Kavida.ai will bring procurement automation agents to Champion AI with the aim of freeing up about half of a buyer's workday by eliminating manual post order and supplier collaboration work. The Kavida.ai PO, RFQ, and Sales agents will become immediately available to QAD | Redzone customers and Kavida.ai's founders, Anam Rahman and Sumit Sinha, will assume leadership roles.

Rahman and Sinha said in a blog post that the company was founded nearly five years ago to address a big issue in manufacturing--many enterprises run on email and spreadsheets.

According to QAD | Redzone, the plan is to add Kavida.ai's procurement agents to its platform to drive manufacturer productivity.

Sanjay Brahmawar, CEO of QAD | Redzone, AI needs to deliver value quickly. "By integrating Kavida.ai’s technology and team, we’re helping our customers unlock value faster — automating critical workflows, improving supply-chain reliability, and giving every buyer, planner, and supplier a powerful digital co-pilot," he said.

Here’s a look at the flow of a Kavida.ai agent.


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CoreWeave's great AI infrastructure race

CoreWeave said it is dealing with ongoing supply chain issues as demand far exceeds capacity and revenue expected in the fourth quarter will slip to the first quarter. Nevertheless, CoreWeave's bet is that self-building its AI infrastructure will be a winning strategy in the future.

Michael Intrator, CEO of CoreWeave, said on the company's third quarter earnings call that there are multiple delays but the biggest issue is at the powered-shell level. Powered shell refers to a facility where the power and exterior are completed, but the interior isn't finished.

"There's plenty of power right now, and we believe that there will be ample power for the next couple of years. But really the challenge is the powered shell," said Intrator.

CoreWeave's third quarter had a bevy of moving parts to consider and also reflected emerging skepticism about capital expenditures for AI infrastructure. Although AWS, Alphabet and Microsoft all said capital spending would continue to surge for AI infrastructure, Wall Street openly questioned Meta's plans. In Meta's case, it could simply be a case of metaverse traumatic stress disorder, but the focus of AI spending is turning to returns.

Consider the following for CoreWeave milestones in what is a frenetic pace of scaling:

  • In the third quarter, CoreWeave had revenue of $1.4 billion, up 134%.
  • Revenue backlog at the end of the third quarter was $55 billion.
  • CoreWeave's will deliver more than 1 gigawatt of contracted capacity to customers within the next 12 to 24 months.
  • The company landed third quarter compute contracts with Meta and OpenAI.
  • A planned merger with Core Scientific is officially off and Intrator said the price was simply too high.
  • CoreWeave is diversifying its stack with the acquisition of OpenPipe, which is a platform for training AI agents, and Marimo, a developer workflow company. CoreWeave also acquired Monolith for an industrial AI play.
  • The company launched a unit to land US government customers and added Jon Jones, an AWS alum, as its first chief revenue officer.
  • CoreWeave also launched AI Object Storage, which optimizes the storage layer for AI workloads. CoreWeave's storage platform has topped $100 million in annual recurring revenue.

However, CoreWeave's buildout comes at a price. In the third quarter, CoreWeave delivered a net loss of $110.1 million, an improvement on the $360 million net loss a year ago. Net interest expense in the third quarter was $310.55 million, up from $104.4 million a year ago. Operating income margin was 4% compared to 20% a year ago.

CoreWeave is obviously betting that if it builds the infrastructure customers will come. "AI adoption is progressing beyond the frontier AI labs and hyperscalers. Broader global demand and our recent large wins are driving diversification of our revenue base," said Intrator, who noted customer wins including CrowdStrike, Rakuten and NASA.

Jones, who was the head of startups and venture capital at AWS, will look to add AI natives that will grow with CoreWeave.

No CoreWeave customer in the third quarter represented more than 35% of the company's revenue backlog. The customer base is still concentrated, but well below the 85% level at the start of 2025. Sixty percent of CoreWeave's revenue backlog is with investment grade customers.

The race

In many ways, CoreWeave symbolizes much of the AI infrastructure market in that there's a race between investor patience and scaling amid fears that overcapacity may loom.

Intrator said supply chain issues may be a risk. "While we are experiencing relentless demand for our platform, data center developers across the industry are also enduring unprecedented pressure across supply chains. In our case, we are affected by temporary delays related to a third-party data center developer who is behind schedule. This impacts fourth quarter expectations," he said.

The customer affected by the current delays agreed to adjust the delivery schedule and extend the expiration date.

CoreWeave said 2025 revenue will be between $5.05 billion to $5.15 billion with adjusted operating income of $690 million to $720 million and more than 850 megawatts of active power.

Nitin Agrawal, CoreWeave CFO, said 2025 capital expenditures will be between $12 billion to $14 billion and the 2026 figure will more than double. Interest expense in 2025 will range from $1.21 billion to $1.25 billion.

Agrawal said:

"In Q4, we will be bringing online some of the largest scale deployment in our company's history. This will have a near-term impact on adjusted operating margin due to the timing difference between when data center costs are first incurred and when we start recognizing revenue.

We expect 2025 interest expense in the range of $1.21 billion to $1.25 billion, driven by increased debt to support our demand-led CapEx growth, partly offset by an increasingly lower cost of capital."

Intrator was asked about CoreWeave's strategy to self-build infrastructure. He said CoreWeave has diversified providers and the ability to self-build data centers makes it a larger player in the supply chain. Intrator added that CoreWeave does work with third-party data center providers, but self-building is "about derisking deliver across the broader portfolio."

"We just look at self-build as an additional piece of the puzzle. It puts us closer to the physical infrastructure. It embeds us deeper into the supply chain around the world so that we have firsthand information," said Intrator. "We just think that you need to be on both sides of this fence in order to be as effective as you can be derisking what is a complicated supply chain environment."

Add it up and CoreWeave is going to be a fascinating business school case study. Is CoreWeave's balance sheet just a pile of debt or growth capital? Can CoreWeave remain differentiated in three to four years? Will CoreWeave build out is AI software stack to play a larger revenue role?

The CoreWeave saga will be a fascinating two- to three-year race. Why? CoreWeave has no debt maturing until 2028.

Constellation Research analyst Holger Mueller said:

"CoreWeave showed outstanding growth with revenue growing 150%+ YoY. It is also showing the skeptics that it is not a money loosing business - as EPS improved year over year. Another quarter like this and CoreWeave should be in the black for Q4 on an adjusted basis. With that demonstrated - the focus needs to shift on CoreWeave managing to keep the growth going with supply chain challenges as it secures capital, delivers data center capacity and runs customer workloads well. At the moment, the first concern with CoreWeave is delivering data centers. We will see if all of this issue is addressed in Q4."
 

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