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Top 5 Takeaways from Dynatrace 2025 | CR Analyst Andy Thurai

Top 5 Takeaways from Dynatrace 2025 | CR Analyst Andy Thurai

Constellation analyst Andy ThurAI recently attended the Dynatrace Perform 2025 in Las Vegas and shares five main takeaways about the future of #observability and AI governance... 

💡 Dynatrace enhances Davis AI for predictive and preventive #AIOps, with AI explaining problems in natural language and auto-generating remediation proposals.
💡 Dynatrace helps #enterprises achieve DORA compliance with automated visibility and a new Compliance Assistance Map.
💡 Dynatrace introduced a new Cloud Security Posture Management (CSPM) solution to unify security across hybrid and multi-cloud environments.
💡 Dynatrace empowers developers with new observability tools, including a live debugger that allows troubleshooting code in production without disrupting servers.
💡 Dynatrace adds new #AI observability features to support rapid adoption of #generativeAI, including guardrail analysis, multi-model tracing, and predictive cost management.

Watch the full announcement analysis below and ask Andy any questions! ?? 🤔

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AI agents aimed at healthcare, but data interoperability still a big issue

AI agents aimed at healthcare, but data interoperability still a big issue

Google Cloud and Microsoft are launching generative AI tools aimed at healthcare by streamlining documentation and searching unstructured data to optimize workflows. Vendors keep rolling out healthcare focused AI and automation, but the industry still struggles with transformation as well as data interoperability.

Google Cloud said it added a feature called Visual Q&A in its Vertex AI Search for healthcare. Visual Q&A is designed to search tables, charts, medical images and diagrams for data. Google Cloud also said Gemini 2.0 models are available in its healthcare offering.

The idea is that physicians will leverage multimodal search and models to get a better view of patient health.

Microsoft launched Microsoft Dragon Copilot, an AI assistant for clinical workflows. The Dragon Copilot will be combined with DAX, a natural language voice dictation platform that includes ambient listening, genAI models and healthcare guardrails. Microsoft acquired Nuance in 2022 for its healthcare foothold and later launched Microsoft Cloud for Healthcare.

According to Microsoft, Dragon Copilot can streamline documentation with multilanguage ambient note creation, surface medical information from trusted sources and automate tasks such as notes, evidence summaries and referral letters. Microsoft's Dragon Copilot can also navigate electronic health records.

The news from Microsoft and Google Cloud are a barrage of releases timed for HIMSS, a large healthcare technology conference. 

  • Oracle launched its Oracle Health Clinical AI Agent, which is a multimodal and screen driven assistant, is available for more than 30 medical specialties. The company said physicians using the AI agent are seeing a decrease of 30% in documentation time. 
  • Salesforce made a similar claim as it launched Agentforce for Health, a library of prebuilt skills and actions for healthcare teams.
  • Epic, which is essentially the ERP system for healthcare, also said it added a host of generative AI tools to make healthcare workflows more efficient.  

AI in healthcare: Are we there yet?

At Constellation Research's Ambient Experience Summit 2025, there were multiple talks about healthcare, AI and patient experiences. See: Constellation Research Ambient Experience Summit 2025: 10 CX takeaways on people, data, AI

Joseph Anzalone, VP of Marketing at GE Healthcare, said the company is transforming from a capital equipment company to one focused on AI applications. GE Healthcare is planning to leverage the 96% of unused data from its devices to enhance clinician experiences.

"We're focusing on the clinician experience now and building AI applications on top of foundation models that will give clinicians usable data and predictive analytics," said Anzalone, who added that healthcare workflows are often slowed by data silos across various systems, insurance providers and channels.

The bet is that AI can help overcome legacy infrastructure.

Kimberly Powell, VP of Healthcare at Nvidia, said digital devices, digital biology and clinical will all be big markets for agentic AI systems.

Powell argued that AI agents will serve as a digital workforce due to shortages. AI agents will succeed because they can sit on top of existing infrastructure. She said:

"I believe agentic AI can overlay on the healthcare system unlike technology in the past. Agents can connect and have a foundation model through an API. Since there's an API, AI agents can navigate autonomously over what is otherwise a antiquated and very complex and disaggregated healthcare system."

Also see: BT150 Spotlight: Centurion Health's Johnny Wu on delivering healthcare in prisons

Data interoperability needed

While these AI visions for healthcare are in progress and impressive, Constellation Research CEO Ray Wang argued in a report that the industry needs to focus on healthcare data interoperability.

Wang said:

"Healthcare systems around the world are facing a confluence of challenges such as aging and declining populations, rising cost of delivery, clinical workforce shortages, and increasing expectations for better outcomes at lower prices. Although healthcare systems have accelerated their digitization projects in an effort to modernize, the results have not shown massive efficiency. One of the biggest opportunities to accelerate digitization and prepare for the Age of AI is improved healthcare data interoperability. In fact, interoperability will play a significant role in driving down costs and improving patient outcomes."

The industry needs to focus on interoperability because "current patients, physicians, and healthcare providers and payors face a constant struggle to integrate, manage, and orchestrate across a hodgepodge of physical and digital functional fiefdoms and silos."

Ultimately, the healthcare industry needs to focus on vendors that support data interoperability, hone data consistency, make interoperability part of governance and leverage standards.

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Qualcomm fleshes out Dragonwing with fixed wireless access platform

Qualcomm fleshes out Dragonwing with fixed wireless access platform

Qualcomm fleshed out its Dragonwing platform as it launched a series of fixed wireless access building blocks designed to enable AI inference use cases as well as industrial applications.

At Mobile World Congress, Qualcomm aimed to stretch beyond its 5G modems, smartphones and PCs to enterprise use cases. Qualcomm launched its Dragonwing branding designed to target enterprises and industrial IoT use cases as well as a partnership with IBM.

The company is looking to expand from handsets, autos, PCs and augmented reality to industrial, networking and other devices.

Qualcomm launched Dragonwing Fixed Wireless Access Gen 4 Elite, a platform that has 40 TOPS Edge AI integration, tops downlink speeds up to 12.5 Gbps and has on-device AI-enhanced traffic classification.

To go along with Dragonwing, Qualcomm launched X85 5G Modem-RF. The Dragonwing FWA Gen 4 Elite platform can deliver long-range 5G mmWave, NTN Satellite communication and dual SIM connectivity along with cellular, Wi-Fi and Ethernet.

The news from Qualcomm is part of a broader strategy to be seen as an AI processor company as more workloads go to the edge of the network. The company launched a series of modems--Qualcomm E41 4G Modem-RF, Qualcomm E51 4G Modem-RF and Qualcomm E52 4G Modem-RF--designed for industrial use cases.

According to Qualcomm, the modems are designed to be deployed in multiple environments such as warehouses, manufacturing plants and other areas with poor signals. The modems can be positioned in any environment and incorporates iSIM technology into the hardware for easy programming.

With the effort, Qualcomm is looking to develop use cases in energy and utilities, retail and autonomous robots.

 

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Will CX suffer from an overreliance on AI?

Will CX suffer from an overreliance on AI?

Although AI--generative, agentic and everything in between--is viewed as a tool that can improve customer experience there is the risk that enterprises may rely too much on the technologies.

At Constellation Research's Ambient Experience Summit 2025, we held a workshop on ways to think different about experiences and address one key challenge. Over-reliance on AI was a big theme as was disjointed customer journeys.

One group noted that CX can be harmed by overreliance on AI. AI can only be so personal and the big workflow issue is figuring out where to insert a human into processes. To date, AI is viewed as a productivity enhancement that can add digital labor and in many cases replace humans.

Yes, CX leaders need to implement AI, but have no control about how it's deployed. In addition, the models can be experimental and simply off the mark. AI isn't a human replacement and it's a big reason why we're hitting #0 every time we call customer service.

Constellation Research analyst Liz Miller noted:

"Let's be honest, if we keep training AI on the nonsense that it's been trained on so far, it is going to get even worse. I do not want my customer experience to be over reliant on AI, because it can be unreliable, lacks human touch, and it is experimental, but it can help when it's deployed."

A few takeaways from the workshop:

  • CX leaders need to think through AI's deficiencies and know the problems they're trying to solve. Is the issue cost efficiency? Is it growth? Is it boosting the lifetime value of the customer relationship?
  • CX leaders need to think through the customer journey and where AI can help. Why are journeys mapped the way they are? It's quite possible that AI and workflow automation may make the customer journey even more disjointed.
  • AI is going to occupy a larger chunk of the customer experience, but don’t go crazy. Humans will have to find the balance needed to blend AI with real-life touchpoints.

One company worth watching on this AI-CX front is Intuit. Speaking on Intuit's fiscal second quarter earnings conference call, CEO Sasan Goodarzi talked about how it was blending AI and humans to create experiences with Intuit Assist.

"We are making strong progress across our platform with our data and AI investments to deliver done-for-you experiences with AI-powered human expertise,” said Goodarzi. “Our focus is on automating tasks, end-to-end workflows, and entire functions, connecting customers to one of our more than 12,000 AI-powered human experts for that last mile or to complete all of the work."

Goodarzi said Intuit is seeing higher conversions across its product line with personalized product experiences. "With the scale of our data and AI capabilities, Intuit Assist is the control tower automating tasks and workflows, with human experts engaging where needed to deliver done-for-you experiences for our customers," said Goodarzi.

Intuit also highlights one of the key takeaways from our CX summit: Data quality is everything. Intuit has invested heavily in its cloud-based data architecture that set the stage for AI.

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Dell Q4 powered by AI servers

Dell Q4 powered by AI servers

Dell Technologies delivered better-than-expected fourth quarter earnings as it continues to see strong demand for AI servers. Shipments for AI servers will hit $15 billion in fiscal 2026, according to the company.

The company reported fourth quarter earnings of $2.15 a share on revenue of $23.9 billion, up 7% from a year ago. Non-GAAP earnings were $2.68 a share.

Wall Street was looking for earnings of $2.53 a share on revenue of $24.57 billion.

Dell Technologies' Infrastructure Solutions Group delivered revenue growth of 22%. Jeff Clarke, chief operating officer, said:

"Our prospects for AI are strong, as we extend AI from the largest cloud service providers, into the enterprise at-scale, and out to the edge with the PC. The deals we’ve booked with xAI and others puts our AI server backlog at roughly $9 billion as of today."

Dell also raised its annual dividend by 18%.

For fiscal 2025, Dell reported earnings of $6.38 a share on revenue of $95.6 billion, up 8% a year ago.

As for the outlook, Dell projected fiscal 2026 revenue growth of 8% to between $101 billion and $105 billion and non-GAAP earnings per share growth of 23%.

Speaking on an earnings conference call, Clarke said:

"We booked deals putting our AI backlog at roughly $9 billion as of today. Our pipeline expanded sequentially and has grown every quarter since the introduction of the 9680. We are seeing continued progress in AI from enterprise customers, albeit still earlier in their journey with sequential growth in both orders and customers. And our engineering services, financing and ability to optimize density and performance per watt are important differentiators for the largest at-scale CSPs and provide very efficient enterprise solutions. In traditional servers, the growth trajectory continues, up double digits in Q4. We've now seen 5 quarters of year-over-year demand."

As for the outlook, Dell CFO Yvonne McGill said:

"IT spending is expected to grow with 3 underlying trends that we see. First, businesses are leveraging AI to enable competitive advantages, and we are seeing that in our opportunity pipeline that continues to expand. Second, data center modernization is well underway with a focus on consolidation and power efficiency. Third, customers are planning to refresh their PC installed base with AI-enabled devices."

By the numbers:

  • Infrastructure Solutions Group (ISG) fourth quarter revenue was $11.4 billion, up 22% from a year ago. Annual revenue was $43.6 billion, up 29%.
  • Servers and networking revenue in the fourth quarter was $6.6 billion, up 37% due to AI servers.
  • AI backlog was $4.1 billion exiting the fourth quarter.
  • Storage revenue was up $4.7 billion, up 5%.
  • Operating income for ISG in the fourth quarter was $2.1 billion.
  • Dell's PC unit revenue in the fourth quarter was $11.9 billion, up 2% from a year ago, with operating income of $631 million. Commercial client revenue was up 5% in the fourth quarter and consumer revenue fell 12%.

Other Dell items worth noting:

US government exposure. "We've had numerous times in our history where a country or a particular segment demand was suppressed for various reasons. We've been able to navigate the cycles, I think, pretty successfully," said Clarke. "Our underlying belief is United States government will need technology. AI plays a pretty significant role in our nation. And I think the demand will materialize. We'll get through whatever is happening today."

Tariffs. Clarke said:

"This is a pretty darn dynamic environment as represented what we heard this morning. It's fluid. We built an industry-leading supply chain that's globally diverse, agile, resilient that helps us minimize the impacts of these trade regulations, tariffs to our customers and shareholders. We've been monitoring this for some time. We've taken our digital supply chain, our digital twins actually using some AI modelling to look at every possible scenario that you might imagine of this country, that country, and restrictions to help us understand how we optimize our network and how we that in the least amount of time at the speed of Dell. And whatever tariff we cannot mitigate, we view that as an input cost. And as our input costs go up, it may require us to adjust prices." 

Nvidia Blackwell margins. Clarke said Blackwell margins remain lower than Hopper. "We're still early. The deals are very large upfront. There's more competitors, so it's a more competitive landscape," said Clarke.  He added:

"This is system design and architecture work. There's an ability to really distinguish our engineering and value add in that step, which is an opportunity for us to extract value and opportunity for us to reduce cost. These aren't reference designs or as we would affectionately call in the engineering community, they're not cookie-cutter designs. We're designing a unique rack, a unique power distribution unit. Our cooling, our manifold, the cold plate, the ability to engineer that and to drive that through the scale of our supply chain are opportunities for us, helping our customers attach with our networking with our storage or opportunities."

Constellation Research analyst Holger Mueller said it remains to be seen how on-premises AI can boost demand. "Dell manages to beat inflation, but not by much, as its client solutions business is still dragging, with even the commercial business barely clocking in at inflation rate," he said. "If Dell’s ISG business keeps growing as it did in the last fiscal, ISG will pass CSG, a milestone for Dell. Dell became more profitable, with EPS up by almost 40%. AI demand keeps being the main driver. The big question is: How strong will the on-premises AI bonanza be in 2025?"

 

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OpenAI's GPT-4.5 has more emotional intelligence, could expand use cases

OpenAI's GPT-4.5 has more emotional intelligence, could expand use cases

OpenAI launched a research preview for GPT 4.5 and perhaps the biggest takeaway is that it can fake emotional intelligence pretty well--potentially better than a few humans we know.

The company outlined GPT-4.5 and noted that early testing shows that interactions with humans are more natural. OpenAI noted:

"Based on early testing, developers may find GPT4.5 particularly useful for applications that benefit from its higher emotional intelligence and creativity—such as writing help, communication, learning, coaching, and brainstorming. It also shows strong capabilities in agentic planning and execution, including multi-step coding workflows and complex task automation."

For collaboration, GPT-4.5 may be a win since it has more EQ.

Key points about GPT-4.5:

  • GPT-4.5 scales unsupervised learning by scaling up compute and data and reduces hallucinations.
  • GPT-4.5 scored better than GPT-4o on collaboration skills.
  • The model doesn't think before it responds.
  • ChatGPT Pro users can select GPT-4.5 today with Pro and Team users getting it next week followed by Enterprise and education users.
  • GPT 4.5 is compute intensive and more expensive than GPT-4o. It is not viewed as a replacement.

Constellation Research’s take

Andy Thurai, analyst at Constellation Research, said:

“OpenAI claims GPT-4.5 will have fewer hallucinations and more accurate writing, programming, and insights.

This is not a reasoning model but an unsupervised learning model. GPT-4.5 doesn’t have a chain of thought like the reasoning models therefore can respond faster. Instead of combining the reasoning models and responding models, OpenAI chose to separate them as the execution costs, and model training costs can be very high for reasoning models such as OpenAI GPT-o1 and o3 mini.

With the models running out of world data, and the model differentiation from the LLM providers becoming less and less differentiated, all of them are looking for ways to stand out. OpenAI has taken the direction of making their chatbot more human. OpenAI claims its EQ is better than other models, meaning the model recognizes tone and intent and responds with empathy rather than just solutions—just like a real human would. With that approach interactions can feel more natural and human like.

In initial testing, GPT-4.5  seems to show strong capabilities in agentic planning and execution, including multi-step coding workflows and complex task automation. However, there is concern in initial tests that it can fake emotional intelligence just like humans would.

However, at the current time these models are very expensive. GPT-4.5 is also restricted only to Pro users for now because of GPU shortage per OpenAI’s claim.”

  • GPT 4.5 pricing: Price Input: $75.00 / 1M tokens Cached input: $37.50 / 1M tokens Output: $150.00 / 1M tokens
  • GPT 4o pricing: Price Input: $2.50 / 1M tokens Cached input: $1.25 / 1M tokens Output: $10.00 / 1M tokens
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Transforming Cybersecurity Through Platformization and AI | IBM and Palo Alto Networks

Transforming Cybersecurity Through Platformization and AI | IBM and Palo Alto Networks

IBM and Palo Alto Networks formed a strategic partnership 🤝 to help organizations transform their #cybersecurity through security platformization and the integration of advanced #AI capabilities...

Constellation analyst Andy Thurai interviewed Tim Van den Heede, VP of Global Security Services Sales IBM, and Kevin Kin, Global VP of GTM and SOC Transformation at Palo Alto Networks, to learn more.

Here's a snapshot of what they covered:

📌 The partnership is focused on helping clients achieve security platformization by combining #technology, service capabilities, and trusted AI. 
📌 They're training 1,000+ experts across both companies on the joint value proposition for clients.
📌 Platformization is crucial to address the complexity and alert fatigue plaguing security operations (the average organization uses 83 different security solutions).
📌 The partnership delivers integrated solutions that simplify security, improve response times, and reduce risk.
📌 AI and #agenticAI are incorporated throughout the offerings to automate threat detection and triage alerts and enhance security decision-making.

Watch the full interview to see how industry collaboration can transform #cybersecurity.

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SAP Business Data Cloud, Data Lakehouse Solutions, CX Trends | ConstellationTV Episode 99

SAP Business Data Cloud, Data Lakehouse Solutions, CX Trends | ConstellationTV Episode 99

Don't miss ConstellationTV episode 99 ??  Holger Mueller and Liz Miller discuss the latest #enterprise news, specifically SAP's introduction of their new Business Data Cloud (BDC) solution. They dive into SAP's strategic shifts, key technology innovations, and how the BDC platform positions SAP for the future. Other topics include updates on Avaya, Amazon Chime, and the latest developments in #quantum computing. 

Next, Holger unpacks his Constellation ShortList criteria for evaluating #data lakehouse solutions - a critical foundation for building next-gen #AI-powered applications.

Finally, Constellation analysts report LIVE from Constellation's Ambient Experience Summit (AXS) in Woodinville, WA, and share the leading themes and takeaways on #CustomerExperience and #EmployeeExperience.

00:00 - Introduction: Meet the Hosts
01:32 - Enterprise Tech News (SAP Business Data Cloud, Avaya, quantum)
15:11 - ShortList Deep Dive - Datalake for Next-Gen Applications
20:34 - LIVE from #AXS2025

This is one episode you won't want to miss - watch here!

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AWS launches Ocelot quantum chip, claims error correction breakthrough

AWS launches Ocelot quantum chip, claims error correction breakthrough

Amazon Web Services launched Ocelot, a first generation quantum computing chip that was developed with the California Institute of Technology.

The news lands as quantum computing developments land almost daily. IonQ is betting on quantum networking. Microsoft launches its new quantum computing processor and approach. Quantinuum blends AI and quantum computing. And meanwhile, the industry awaits a Nvidia GTC quantum computing panel with Jensen Huang.

Recent headlines include:

AWS said Ocelot can reduce the costs of quantum error correction by up to 90%. According to AWS, "Ocelot represents a breakthrough in the pursuit to build fault-tolerant quantum computers capable of solving problems of commercial and scientific importance that are beyond the reach of today’s conventional computers."

The findings behind Ocelot were published in a peer-reviewed research paper in Nature. Key details include:

  • Ocelot is based on superconducting quantum circuits.
  • It has a scalable architecture designed to lower error correction overhead.
  • Ocelot includes the first implementation of a noise-biased gate, which tunes out errors.

Amazon is catching up with its own quantum computing hardware. Since quantum computing is going to be consumed almost solely in the cloud, hyperscalers are developing their own systems and offering choices and entry points to pure play providers.

Constellation ShortList™ Quantum Computing Platforms | Quantum Computing Software Platforms | Quantum Full Stack Players

In a statement, AWS said the design of Ocelot includes the 'cat qubit,' which suppresses certain forms of errors to reduce the resources needed for correction. AWS' quantum chip can be manufactured and scaled like a microelectronics processor. This scalable quantum chip format is also the big takeaway from Microsoft's Majorana 1 launch.

Oskar Painter, AWS director of Quantum Hardware, said practical quantum computers are available for real-world applications. "Quantum chips built according to the Ocelot architecture could cost as little as one-fifth of current approaches, due to the drastically reduced number of resources required for error correction," said Painter. "Concretely, we believe this will accelerate our timeline to a practical quantum computer by up to five years.”

Constellation Research's take

Holger Mueller, analyst at Constellation Research, said:

"AWS has entered the quantum space with its error correction capabilities announced back at Reinvent:2023, and is now moving backwards in the value chain and designing its first Quantum chip. No surprise that it has superconducting like all the promising announcements of the last 6 months. What stands out in the AWS design is the division of qubits for separate functions. This separation is also an AWS tradition if one considers the Nitro architecture. It will be interesting to see how the new platform will perform and potentially prove that specialized qubits on one chip are the way forward for quantum computing."

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IonQ doubles down on quantum networking, names new CEO as it eyes scale

IonQ doubles down on quantum networking, names new CEO as it eyes scale

IonQ is doubling down on quantum networking with an acquisition, diversifying globally and has a new CEO along with fourth quarter results and plans to raise more capital.

For one of quantum computing's highfliers that's a busy afternoon and a lot of transition going into a new fiscal year.

IonQ's busy news day was framed by a leadership change. IonQ named Niccolo de Masi CEO with Peter Chapman becoming Executive Chair. Chapman will focus on strategy and enterprise adoption. De Masi was already on IonQ's board and previously was CEO of the SPAC that hatched IonQ in 2021.

On a conference call, de Masi and Chapman took questions and covered topics seamlessly. "This evolution will allow me to spend more time focused on our strategic customer relationships and the development of quantum AI," said Chapman, who noted de Masi has been involved in IonQ's strategic direction and growth plans from the beginning. IonQ also named Gabrielle Toledano, Chief People Officer of Tesla, to its board.

"There's a lot of continuity, and there's obviously an opportunity for the two of us to tackle two businesses, which are growing at inflection points that are truly historic," said de Masi. "There are no changes in strategic direction, because Peter and I have been working together closely to set the strategic direction the last five years, and we'll continue to do that."

And then there's the bet on quantum networking. IonQ has focused on quantum computing systems, but is betting that quantum networking can be just as big of a market. The company said it will buy ID Quantique in a move that will boost its quantum networking business. In November, IonQ bought Quibitekk.

The purchase of ID Quantique gives IonQ more quantum networking patents and diversifies the company's global footprint with expansion in South Korea. IonQ also forged a partnership with SK Telecom. With 300 patents from ID Quantique, IonQ now has 900 patents that are granted or pending.

Chapman explained:

"Our goal is to build a suite of products that enable secure quantum communication in all forms, from satellites to ground stations, across existing telecommunication fiber infrastructure, to drones on a battlefield. Those following IonQ closely will note that we are building out the key component technologies for the telecom and defense sectors. With the pending addition of ID Quantique and the completed addition of Qubitekk, we will partner with their existing blue chip customers, which include SK Telecom and the Electric Power Board of Chattanooga. These customer relationships allow us to test new hardware and applications in real-world environments."

Q4 results, new capital, new use cases

IonQ reported fourth quarter revenue of $11.71 million with a net loss of $202 million, or 93 cents a share. IonQ's net loss was inflated by the fair value of warrant liabilities. When IonQ shares go higher so do the warrant liabilities.

For 2024, IonQ delivered revenue of $43.07 million, nearly double from a year ago. The net loss was $331.65 million for 2024.

IonQ projected 2025 revenue of $75 million to $95 million with between $7 million to $8 million in the first quarter. IonQ also said it would offer $500 million in stock to raise cash that will be used to expand the quantum networking business.

Chapman said IonQ's partnership with AstraZeneca is showing promising results in chemistry modeling. An Ansys partnership puts IonQ in the computer-aided engineering market. “We believe that 2025 will, in fact, be the year of quantum, one in which you see both public and private institutions realize that computing and networking game will be forever changed by IonQ systems,” said Chapman. “With commercial advantage right around the corner, the inflection point that everyone has been waiting for is not far behind it.”

In the weeks ahead, IonQ will outline commercial advances, appear at Nvidia GTC and launch new quantum computing metrics as it depreciates its AQ performance benchmark, said Chapman. 

More quantum computing:

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