Tools & Platforms
Memory And Design Advances From The AI Infra Summit
This article discusses memory and chip and system design talks at the 2025 AI Infra Summit in Santa Clara, CA by Kove, Pliops and Cadence.
John Overton from Kove gave a talk about their Linux based memory software that runs on any hardware and allows sharing memory between servers to increase memory utilization, CPU and GPU utilization. He pointed out that GPUs have been scaling as have CPUs, but conventional memory systems do not, leading to overprovisioning in servers and processing bottlenecks.
He said that Kove SDM software can be installed in a system in 15 minutes and allows unlimited memory accessed from virtualized elastic memory pools across servers and supports up to 64PiB of DRAM per process. He also said that the software can hide latency, making memory look local to a CPU, even when it isn’t. He said this can work across Infiniband and RoCE fabrics.
In particular he said Kove SDM can hide latency between memory that is over 150m away. The image below shows the resulting AI performance improvements.
Kove AI performance improvements
Kove
He said that for AI inference, with Kove it can run 3-5X faster and that this had been shown working with partners such as Redhat and SuperMicro to show key-value, KV, cache at scale. These are results from benchmarks using Redis and Valkey. The slide below summarizes their claims for ROI improvements using Kove. He also said it can improve vector search and enable larger concurrent processing.
Kove SDM return on investment
Kove
Pliops was showcasing its XDP LightingAI at the Summit, a GenAI native memory stack to power interfence and retrieval workloads for hyperscale and enterprise applications. The product consists of an ASIC, the Extreme Data Processor, XDP, a software stack and distributed nodes and uses a GPU-initiated Key-Value I/O interface.
According to Pliops, deploying Pliops XDP LightningAI in data centers offers significant cost savings. Instead of needing four times as many GPU servers to support 4X more users for LLM inferencing, you can maintain your existing GPU infrastructure and add XDP LightningAI servers. This results in a 67% optimization in rack space, a 66% reduction in power consumption, 58% annual OpEx savings, and a 69% decrease in initial investment costs.
Pliops is collaborating with Tensormesh, inference optimization software. The company says combining LightningAI memory acceleration with Tensormesh’s shared KV cache architecture results in fast time-to-first token and GPU savings across multi-GPU clusters.
Another interesting talk was that of Charles Alpert from Cadence. Cadence is an electronic design software company that enables device and system simulation and has been doing this for decades. He spoke about the various challenges in AI infrastructure as shown in the slide below. These include energy consumption—driving GW data centers, thermal management and the time to operationalize that infrastructure.
AI infrastructure challenges
Cadence
He talked about how this can be improved by adding AI for design to design for AI to create continuous improvements in data centers and the devices that work with them in a virtuous cycle. Cadence has tools for data center design as well as its traditional semiconductor design and in semiconductors their tools can also work with 3D stacks of die and include Multiphysics digital twin simulation. He said that over half the chips built today use AI technology and that this will accelerate to 90% in the next few years using agentic AI as shown below.
AI driven chip design trends
Cadence
Agentic AI should lead to levels of autonomous design, similar to those used for talking about autonomous driving as shown below. In his talk he went into detail on each of these levels for increasing autonomy.
Levels of autonomous chip design
Cadence
He also talked about how these new EDA tools with multi-physics capability will enable designing 3D devices made from stacking semiconductor die, often called heterogeneous integration as shown in the figure below. Doing this requires massive system level integration and is resource intensive.
AI driven 3D die integration design
Cadence
In particular he pointed out that these 3D workloads will benefit from improvements in the number and capability of GPUs.
Last year Cadence announced its Palladium Emulator, shown below. Jensen Huang from Nvidia called it an essential tool for designing NVIDIA’s most advanced chips, including the Blackwell series.
Cadence Palladium emulator
Cadence
Cadence has expanded this technology beyond chip design towards creating digital twins of data centers including all the functional components. Their Millennium M2000 system enables much faster chip design as well as system design. These are tools for Cadence’s Digital Twin Ecosystem for data center design as shown below.
Cadence Reality digital twin ecosystem
Cadence
Kove talked about massive memory sharing to accelerate AI inference, Pliops was showing their AI-native memory stack and Cadence talked about complete digital twin data center design at the 2025 AI Infra Summit.
Tools & Platforms
How Mastercard’s (MA) AI-Powered Payments Push and Tech Partnerships Have Changed Its Investment Story
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In the past week, Mastercard announced a suite of AI-powered payment products and developer tools, expanded consulting services, and new collaborations with global technology leaders such as Stripe, Google, and Ant International, supporting a rollout of its Agent Pay program to all U.S. cardholders by the end of the holiday season.
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This initiative positions Mastercard at the forefront of advancing secure, intelligent commerce by making AI-enabled payments and agentic capabilities accessible and scalable for digital merchants and platforms worldwide.
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We’ll now examine how Mastercard’s push into AI-powered payments and its collaborations with technology partners could reshape its investment narrative.
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If you’re a Mastercard shareholder, you likely believe in the ongoing digital shift in payments, the company’s powerful network effects, and its ability to grow by expanding into new revenue streams like AI-powered services. The recent launch of AI tools and expanded partnerships has the potential to support growth drivers, especially deeper collaboration with tech partners for value-added services, but the most important short-term catalyst remains increasing digital and e-commerce transaction volume. For now, these AI announcements don’t fundamentally alter the biggest risk: faster adoption of alternative payment rails in key emerging markets.
Among the recent announcements, the release of Mastercard’s On-Demand Decisioning (ODD) stands out. This solution offers financial institutions more direct control and flexibility over transaction approvals, supporting the broader catalyst of helping partners automate, personalize and scale digital payments. As Mastercard continues to expand its value-added services beyond core payments, such tools could help reinforce its differentiated service offering.
However, investors should be aware that while Mastercard accelerates innovation, an even faster shift by consumers and merchants to alternative payment options could…
Read the full narrative on Mastercard (it’s free!)
Mastercard’s outlook anticipates $42.6 billion in revenue and $19.9 billion in earnings by 2028. This requires a 12.1% annual revenue growth rate and a $6.3 billion increase in earnings from the current $13.6 billion.
Uncover how Mastercard’s forecasts yield a $644.55 fair value, a 11% upside to its current price.
Tools & Platforms
Efficiency, Ethics, and 2025 Outlook
In the rapidly evolving world of artificial intelligence, a subtle transformation is underway, one that promises to redefine how we interact with technology. AI agents, autonomous software entities capable of performing tasks independently, are quietly infiltrating everyday digital routines, from managing emails to optimizing workflows. Unlike the flashy chatbots of yesteryear, these agents operate in the background, learning from user behavior and executing complex sequences without constant human oversight. This shift, as detailed in a recent HackerNoon article, highlights how companies like OpenAI and Anthropic are pioneering systems that don’t just respond to queries but anticipate needs, turning passive tools into proactive companions.
The appeal lies in their efficiency. Imagine an AI agent that scans your calendar, books flights based on past preferences, and even negotiates better rates—all while you’re asleep. This isn’t science fiction; it’s the reality emerging from advancements in machine learning and natural language processing. Industry insiders note that these agents are built on large language models enhanced with decision-making algorithms, allowing them to handle multi-step processes. For instance, Google’s Project Astra, powered by Gemini 2.0, integrates multimodal inputs like text and images to assist in real-world tasks, such as identifying books on a shelf and recommending the best one, according to a Zilliz blog post.
Autonomy Meets Everyday Utility: How AI Agents Are Scaling Up in 2025
As we move deeper into 2025, expectations for these agents are tempered with realism. IBM’s insights suggest that while hype surrounds “agentic AI,” practical implementations will focus on niche applications rather than universal overhauls. In workplaces, agents are automating repetitive tasks, freeing humans for creative endeavors. Microsoft’s trends report predicts AI agents will simplify life at home and on the job, driven by improved reasoning and memory capabilities. “AI is already making the impossible feel possible,” notes Chris Young, executive vice president at Microsoft, emphasizing the shift from experimentation to adoption.
Yet, challenges persist. Ethical concerns, including data privacy and decision biases, loom large. A Medium piece from Lightcap AI warns that while open-source models democratize access, they also raise risks of misuse. In marketing, MarTech predicts agents will deliver personalized insights, analyzing consumer data to refine campaigns autonomously. This evolution is echoed in fintech, where AI-driven banks like Malaysia’s Ryt Bank use agents for real-time financial decisions, as reported in AI News updates.
From Hype to Integration: Real-World Impacts and Future Trajectories
The integration of AI agents into digital life is accelerating, with posts on X highlighting their potential to dominate sectors like DeFi and content creation by year’s end. Users speculate that agents could manage on-chain trades or even generate indistinguishable social media content, pointing to a future where digital interactions blur with human ones. However, experts caution against overreliance; a WebProNews article on 2025 tech trends underscores the need for ethical frameworks amid agentic AI’s rise, including risks in autonomous warfare and digital deception.
In healthcare, agents are analyzing patient data to aid diagnoses, while in customer service, Vertu’s trends report details hyper-personalized phone interactions via AI. Alibaba’s new GUI automation tools, as covered in AI Agent Store news, enable agents to navigate interfaces seamlessly, transforming user experiences. This quiet revolution, far from the bombast of early AI announcements, is reshaping productivity. As Bindu Reddy’s X post asserts, organizations may deploy hundreds of agents for tasks like workflow automation, fundamentally altering enterprise operations.
Navigating Risks and Opportunities: The Balanced Path Forward
Despite the promise, not all developments are seamless. Anthropic’s Chrome extension for Claude allows browser manipulation, raising security questions, per Crescendo AI news. Dotcominfoway’s blog explores opportunities in business, citing stats like potential $100 million savings from agent-driven efficiencies in supply chains. For insiders, the key is balancing innovation with oversight—ensuring agents enhance, rather than disrupt, human agency.
Looking ahead, Gartner’s designation of agentic AI as a top 2025 trend, as noted in various analyses, signals broader adoption. From autonomous agents in cybersecurity to personalized financial advisors, the trajectory is clear: AI agents are embedding themselves into the fabric of digital existence, promising a more efficient, if more automated, future. As discussions on platforms like Medium and X evolve, the consensus is that 2025 will mark the year these silent operators truly come of age, redefining what it means to live digitally.
Tools & Platforms
Arm Holdings Invests £100M in Bristol AI Chip Design Center, Creating 100 Jobs
In a move that underscores the United Kingdom’s ambitions to solidify its position as a global hub for semiconductor innovation, Cambridge-based Arm Holdings has announced plans to establish a new chip design center in Bristol. This development, reported by the BBC, involves an investment of up to £100 million over the next five years and aims to create around 100 high-skilled jobs in the region. Arm, renowned for its energy-efficient processor designs that power billions of devices worldwide, is targeting advancements in artificial intelligence, automotive technologies, and data centers with this expansion.
The Bristol site will focus on developing next-generation central processing units (CPUs) and graphics processing units (GPUs), building on Arm’s existing ecosystem that includes partnerships with tech giants like Apple, Qualcomm, and Samsung. This initiative comes at a time when the global chip industry is grappling with supply chain disruptions and geopolitical tensions, particularly around U.S.-China trade relations. By expanding domestically, Arm is not only diversifying its operations but also tapping into the UK’s growing pool of engineering talent, much of which has been nurtured by universities in the southwest of England.
Strategic Growth Amid Global Challenges As the UK government pushes forward with its Modern Industrial Strategy, initiatives like Arm’s Bristol center align closely with national goals to boost the digital economy to £1 trillion by the end of the decade. Recent reports from GOV.UK highlight the sector’s potential, emphasizing investments in AI, quantum computing, and cybersecurity to drive economic growth. Industry insiders note that this move by Arm could catalyze further investments in the region, potentially transforming Bristol into a semiconductor hotspot akin to Cambridge’s Silicon Fen.
However, challenges persist. Talent shortages remain a critical hurdle, with the UK facing competition from Silicon Valley and emerging Asian tech hubs. Posts on X, formerly Twitter, from users like those at McKinsey & Company, discuss how frontier technologies such as agentic AI are redefining business, yet underscore the need for skilled workers in design and electronic design automation (EDA). Arm’s expansion addresses this by partnering with local institutions to train engineers, but broader systemic issues, including visa restrictions for international talent, could impede progress.
Innovation at the Edge of Computing Looking ahead to 2025, trends identified in McKinsey’s technology trends outlook point to the integration of AI with edge computing as a pivotal shift. Arm’s designs are particularly suited for this, enabling real-time decision-making in devices from autonomous vehicles to smart factories. X posts from tech analysts highlight how combinations of AI, IoT, and 5G are expanding strategic applications, with companies like Tesla and Amazon leading the charge in innovation management.
The UK’s digital sector already contributes over £150 billion annually to the economy, according to Statista, employing 1.7 million people. Arm’s Bristol venture could amplify this by fostering collaborations in emerging fields like bio-based materials and decentralized renewable energy, as speculated in forward-looking X discussions about post-2025 sectors. Yet, geopolitical frictions and supply chain fragility, as noted in recent UKHotViews analyses, pose risks, with export controls potentially affecting chip production.
Policy Support and Future Prospects The Labour government’s tech policy for 2025, detailed in Taylor Wessing’s insights, emphasizes regulatory frameworks to support digital growth while addressing ethical concerns in AI. Arm’s expansion benefits from such policies, including grants for R&D in critical technologies. Industry observers on X, such as those from Smart Sync Investment Advisory Services, warn of rising tech complexity and cost pressures, yet view semiconductors as the “new oil” powering everything from quantum computing to electric vehicles.
To mitigate these, Arm is investing in domestic silicon ramps, with reports indicating shipments of advanced chips like Huawei’s Ascend series influencing global markets. This positions the UK to compete in the intensifying global tech race, as outlined in Digital Watch Observatory. For industry insiders, the key takeaway is clear: strategic expansions like this not only bolster economic resilience but also pave the way for breakthroughs in AI-driven diagnostics and telemedicine, ensuring the UK’s tech sector remains at the forefront of innovation.
Economic Ripple Effects and Long-Term Vision Beyond immediate job creation, Arm’s Bristol center is expected to stimulate local economies through supplier networks and startup incubators. Data from Financial Times archives show how tech growth has spread beyond the southeast, with “tech towns” like Burnley benefiting from similar booms. Current sentiment on X, including posts from Icetea Software, emphasizes AI’s role in reducing latency through edge computing, which could enhance sectors like agri-tech and mental health apps.
Ultimately, as the UK navigates post-Brexit realities, investments in homegrown tech talent and infrastructure will be crucial. With McKinsey projecting 13 tech trends shaping 2025, including multilingual generative AI, Arm’s move exemplifies proactive adaptation. By leveraging its strengths in efficient chip design, the company—and the nation—stands poised to thrive in an era where digital innovation drives sustainable growth and societal benefits.
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