• Nvidia's Olympus core architecture prioritizes single-thread IPC over frequency, using a 10-wide decode front end, deep out-of-order mid-core, and a graph prefetcher tuned for agentic AI's branch-heavy, pointer-heavy workloads
• Vera trades chiplet-style core density for a monolithic 88-core die and single-NUMA-per-socket design, a deliberate bet on agentic AI workloads that Nvidia's own engineers admit comes at the expense of legacy workload performance
• Self-reported SPEC CPU 2026 results by Nvidia paint a per-core advantage figure of anywhere between 70% and 80% versus AMD's EPYC 9755 server CPU

Nvidia's Vera CPU has a lot to prove, representing the company's first real attempt at the AI server CPU market, where traditional vendors Intel and AMD, along with third-party Arm-based providers, are all gunning for a piece of an increasingly lucrative data center pie.

To that end, Nvidia has published its most detailed technical account yet of the chip, promising substantial performance gains over the competition. Vera is the company's first server processor built around a fully in-house core design, a departure from the stock Arm cores that powered its Grace predecessor.

As Vera heads toward general availability in the second half of 2026, Nvidia is making its case on a specific front: not raw core count, but sustained per-core performance under load, the metric it argues matters most for agentic AI.

What's actually under the hood of Nvidia's Vera CPU?

At the core of every Vera CPU is Olympus, Nvidia's first custom server core, built to the Armv9.2 instruction set but designed in-house rather than derived from Arm's stock Neoverse designs, as its predecessor, Grace, was.

Nvidia's second-generation data center CPU is a completely reworked design built around a single goal: to lead in agentic workload performance.

Rather than following Intel and AMD down the chiplet route, Nvidia packs all 88 cores (176 threads) onto a single monolithic die, with a dual-socket configuration delivering 176 cores and 352 threads in one system.

Nvidia has detailed the core design extensively, and several publications have since dug into the microarchitecture. The front end runs a 10-wide decode engine paired with a neural branch predictor that can resolve up to two taken branches per cycle, designed to handle the large instruction footprints and irregular control flow of interpreters, compilers, and agent runtimes.

The mid core combines a wide rename-and-allocation engine with a large reorder buffer and dependency-breaking techniques including memory renaming and value prediction.

The execution engine schedules dynamically across integer, vector, floating-point, cryptographic, load, and store resources, while the cache subsystem adds a graph prefetcher targeting the pointer-chasing access patterns that defeat conventional streaming prefetchers.

That design has not gone unanswered. AMD has countered with estimated figures for its 256-core Zen 6 "Venice" part, claiming a 3.3x rack-level advantage over Vera, though those numbers are extrapolated rather than measured.

AMD responding first isn't surprising. Within x86, it continues taking ground from Intel, reaching 33.2% of x86 server CPU shipments in Q1 2026 per Mercury Research, up from 27.2% a year prior.

With Arm reporting that its architecture now accounts for roughly 50% of CPU compute among top hyperscalers, competition is building from several directions at once. Vera may well set a new bar for agentic AI.

• Copenhagen-based Triton Depth, founded in 2025 by three DTU engineering students, has raised €1 million in pre-seed funding
• It aims to address one of the EU's most underserved security concerns: the seabed, as Baltic cable sabotage, shadow-fleet activity, and underwater drone warfare are increasingly growing concerns
• Triton Depth intends to build a scalable network of passive acoustic sensors it calls 'Triton Nodes' to address the issue, leveraging AI to identify vessels and objects in real time

A three-man Danish company founded by students is venturing into a somewhat interesting industry for an EU-based startup: underwater defense.

Triton Depth has received €1 million in pre-seed funding from investors including London-based The Creator Fund and Denmark's state-owned Export and Investment Fund (EIFO), with aims to focus on acoustics to answer what is arguably Europe's biggest security threat in the days to come: drone-based naval warfare and sabotage.

With growing concerns about the vulnerability of the European Union, and by extension, Denmark, to a variety of sea-borne threats, EIFO's investment in Triton Depth might be more than just a value play, but a hallmark of a realization that it needs to tend to its own defense needs even as NATO continues to meander, with the US proving to be a volatile partner of late, to say the least.

Using affordable dual-use acoustic technology as the first line of defense

Triton Depth's approach is appealing for a domestic defense industry that does not share the budgets that larger naval players such as the US, Russia, or China possess: it is simple, yet elegant in its premise, and even partial wins when it comes to its claims would go a long way to safeguard Denmark and the EU's regional interests.

Triton Depth's approach centers around the use and deployment of its 'Triton Nodes', a scalable cluster of low-maintenance passive acoustic sensors that measure sound underwater before feeding information back to an AI model that assesses and classifies signatures it detects in real time.

The company intends to market its product line as a dual-use technology play, with CEO and Co-Founder Carl Borg stating that they aim to build "the intelligence layer for the ocean" for both civilian and defense use cases.

The focus on defense stems from Denmark's own vulnerabilities in the Baltic Sea, which has previously suffered significant economic damage from sabotage, including the destruction of Nord Stream 1 and 2.

With an increasing share of its critical infrastructure, including power interconnectors, data cables, and offshore wind, lying underwater, it could be argued that EIFO's investment is the Danish state safeguarding its own maritime security and intelligence interests by investing in an intelligent tripwire for the future.

Other European governments are also actively seeking scalable, affordable ways to monitor coastal and subsea infrastructure, even as Nordic defense budgets continue to rise, with Triton Depth among many defense infrastructure companies poised to benefit from a renewed focus on maritime security in the region, even as acoustics are seen as a reliable metric to monitor for a variety of infrastructure plays.

• An internal DHS readout shows analysts twice dismissed intrusion alerts on the HSIN information-sharing network as false positives
• This effectively gave hackers roughly three weeks of undetected access before a breach was declared on June 4 2026
• The as-yet anonymous attackers altered server files, ran malicious code through a legitimate web-server program, deleted logs, installed backdoors, and stole credential files

Hackers managed to find their way into the US Department of Homeland Security's primary information sharing platform, gaining unfettered access to the HSIN network that hosts unclassified information that multiple US agencies and international rely on.

The hack allowed the attackers to modify server files, run malicious code and steal credential files while installing backdoors and deleting logs to remove their digital footprint.

Their movements were flagged twice by automated systems and analysts in May 2026, before being dismissed as a false positive each time before an active breach was declared a month later.

Bad timing meets bad security practices?

The timing and specifics of this intrusion are, in particular, details which could prove to be embarrassing for the US government.

Not only does the HSIN network serve as a key intelligence-sharing tool for both domestic and international partners during the FIFA World Cup, but it also hosts information on other major events, such as America250.

The fact that the hack was picked up not once, but twice by flags before being dismissed as a false positive raises competency concerns for an instance that has already sparked interest, with the House Homeland Security Committee staff having already requested a briefing on the intrusion.

The DHS, for its part, is downplaying the incident, with a spokesperson confirming it but characterizing it narrowly: the department is "aware of a recent cyber incident involving a specific, unclassified legacy information sharing environment" and states there is no indication that classified networks were affected.

This viewpoint is countered by Senate Intelligence Committee Vice Chairman Mark Warner, who argued the platform's sensitivity outstrips its classification level, saying that the information in HSIN, "while not classified, is highly sensitive, and its exposure risks national security."

Investigators have yet to identify or assign blame to a particular hacking group or organization, adding to the chaos in determining motive. The hackers have deleted logs on servers, which only adds to the confusion here.

Major implications

The important question, perhaps, is not how the breach happened, but why confusion and mischaracterization of the security lapse allowed it to become a much bigger issue than it would have been if it had been contained from the start. Despite security flags and analysts highlighting the breach as early as the 15th of May, the hackers essentially had free rein to operate until at least the 3rd of June thanks to initial reports being dismissed as false positives.

HSIN as a platform handles event security planning, interagency coordination, threat information, and details on persons of interest. Whether any of that material was actually copied remains unknown. Investigators have not determined what, if anything, was exfiltrated, though the theft of credential files is itself telling: attackers who steal credentials are, almost by definition, trying to reach systems and accounts beyond their initial foothold.

This is not the first time HSIN has been compromised, with two documented previous incidents, including a compromised account in 2009 and misconfigured access in 2023, that have resulted in intentional and unintentional breaches of the network.

The issue is only exacerbated by the fact that the DHS, along with its cybersecurity agency, CISA, has absorbed significant workforce cuts over the past year, potentially weakening its defenses against sophisticated hacks that require manual human intervention or oversight to detect, even when the correct flags (which triggered as intended) are already in place.

Such manpower shortages have also been politically polarizing in the US Congress and may be highlighted when the department provides more detailed information about the hack in the coming days, even as the Pentagon deals with its own OPSEC issues that are also being aired in the same forum.

Via DefenseOne

• ETH Zurich quantum chip sees superconducting qubit act as CPU and the vibrational modes of a fingernail-width acoustic resonator serve as quantum RAM
• The approach borrows from classical computer architecture as it completely flips the script on how modern quantum computing might store short-term data
• The team demonstrated a universal gate set and ran small instances of the quantum Fourier transform and period finding

A guitar string essentially stores a note based on how it vibrates, and if one plucks it differently, an entirely different note plays.

A team of researchers at ETH Zurich has leveraged the same principle to build a quantum chip that stores information by replacing the string with microscopic acoustic resonators.

This allows the chip to increase its working memory significantly, essentially increasing the storage capacity, a prohibitively expensive commodity in quantum computing, significantly.

A vibrations-based quantum storage play

ETH Zurich's research is led by quantum physicist Yiwen Chu, who used tiny mechanical vibrations to both store and process information. The vibrations, however, go far beyond the range of human hearing, happening inside a quantum chip where they essentially replace or complement the working memory of a quantum computer.

The study, published by the Hybrid Quantum Systems group, lists Professor Yiwen Chu, along with doctoral students Yu Yang and Igor Kladarić, as lead authors and focuses on replicating the division of labor seen in a classical computer.

A superconducting transmon qubit serves as the CPU, while the working memory (the quantum equivalent of RAM) is a high-overtone bulk acoustic wave resonator, or HBAR, whose many vibrational modes each serve as a memory slot.

The Qubit essentially swaps a quantum state from a vibrational mode (reads it, in classical computer terms), manipulates it (modifies it), and swaps it back (writes it). This makes for a unique configuration that most modern quantum computers do not follow, in which processing and storage are two distinct segments; most designs treat both memory and compute similarly.

The approach has advantages, however: acoustic waves have wavelengths roughly a hundred thousand times shorter than electromagnetic ones, allowing an entire quantum chip to be extremely small, as the research team states, even if the actual computer will be many orders of magnitude larger.

The chip has passed stress tests, including a proof of feasibility, which also included testing using two of the most commonly used methods to benchmark a quantum computer: the quantum Fourier transform and a period-finding algorithm.

The endgame here, as noted by the research team, is quantum random-access memory (QRAM), which would allow modern quantum computers to access a much larger store of quantum memory than current specifications allow. Whether this pans out depends on both the scalability of the approach and the computational power in play.

• Vyriy 15 FPV with The Fourth Law's TFL-1 AI guidance reportedly struck Russian logistics 68 miles (110 KM) away
• Ever-innovating Ukrainian drone industry continues to achieve economies of scale even as it becomes a growing threat to Russian advances
• With a payload capacity of 8kg and the ability to be equipped with a thermal imaging module as well as electronic warfare deterrence, it offers an interesting alternative to comparable fixed-wing drones that cost thousands of dollars

Basic FPV drones are hardly a new thing in a market flooded with hundreds, if not thousands of options that can cost as little as $100 to 200, but the Russia-Ukraine conflict might have upped the ante on affordability for a different kind of UAV that leverages the same tech: attack drones.

The Vyriy 15 is a self-styled "kamikaze drone" by the company that offers a stated strike range of 40-70km with up to a 8kg payload in tow which can be retrofitted with a thermal imaging module as well as an extended band VTX module to make jamming it harder.

With a control range of up to 30KM and a flight duration of 20 minutes (with a payload) and a cruising speed of 60-100 km/h, its not the most technologically advanced drone out there, but at its purported price tag of $500, it doesn't need to be.

An FPV strike record backed by AI

On the 10th of July, Yaroslav Azhnyuk, the CEO of Ukrainian autonomy developer The Fourth Law, announced on X what he called "a new FPV strike record": a Vyriy 15 quadcopter, flown by Ukraine's 5th Border Guard Detachment and fitted with his company's AI terminal-guidance module, had flown 110 km (68 miles) to strike a Russian logistics target.

This is both a significant achievement for Ukraine's domestic drone industry and a key indicator of how fast the Russia-Ukraine war has turned into one of attrition, with supply lines becoming increasingly targeted to prevent significant advances in either direction.

It also showcases how AI on the battlefield is shaping the conflict: the Vyriy 15 is, by default, a manually controlled drone that would otherwise need an operator or a relay to be closer to the theater of war.

The competition is American-made Hornets, fixed-wing drones that can cost upwards of $5,000, a 10-fold increase in cost for an already cash-strapped Ukrainian military that is increasingly looking towards localized solutions.

The optional AI module used to set the record is The Fourth Law's TFL-1, a machine-vision terminal-guidance module that operates on a fire-and-forget principle: once the operator visually designates a target, an onboard computer takes over the final approach, essentially countering Russian jammers that would otherwise disrupt a video link.

If Ukraine manages to mainstream such warfare in the future while cutting costs down to a tenth of what they do right now, reliably striking as deep as 100km into enemy territory while proving difficult to jam or costly to intercept, drones like the Vyriy 15 could signal an evolution in the modern battlefield even as aggression with low-cost drone swarms is already being rewarded in other conflicts such as the US-Iran war.