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Jensen Huang predicts Nvidia AI chip revenue will hit $1 trillion by 2027

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“The inference inflection has arrived,” Huang said during the keynote, framing the next stage of the AI boom around systems designed not just to train models but to run them at massive scale.
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The Pentagon is developing alternatives to Anthropic, report says

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After their dramatic falling-out, it doesn’t seem as though Anthropic and the Pentagon are getting back together.

Instead, the Pentagon is building tools to replace Anthropic’s AI, according to a Bloomberg conversation with Cameron Stanley, the chief digital and AI officer at the Pentagon.

“The Department is actively pursuing multiple LLMs into the appropriate government-owned environments,” he said. “Engineering work has begun on these LLMs, and we expect to have them available for operational use very soon.”

Anthropic’s $200 million contract with the Department of Defense (DOD) broke down over the last several weeks after the two parties failed to come to an agreement over the degree to which the military could obtain unrestricted access to Anthropic’s AI.

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While Anthropic sought to include a contractual clause that prohibits the Pentagon from using its AI for mass surveillance of Americans or to deploy weapons that can fire without human intervention, the Pentagon didn’t budge. Instead, OpenAI swooped in and made its own agreement with the Pentagon. The Department of Defense — known under the Trump administration as the Department of War — also signed an agreement with Elon Musk’s xAI to use Grok in classified systems.

It makes sense, then, why the Pentagon would be working on phasing Anthropic’s technology out of its workflows. While some reports said there was a small possibility that Anthropic would reconcile with the Pentagon, this news suggests that the government is preparing to forge ahead without them.

In fact, Defense Secretary Pete Hegseth has declared Anthropic a supply-chain risk, a designation usually reserved for foreign adversaries, which bars companies that work with the Pentagon from working with Anthropic as well. Anthropic is challenging this designation in court.

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Nvidia’s agentic AI stack is the first major platform to ship with security at launch, but governance gaps remain

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For the first time on a major AI platform release, security shipped at launch — not bolted on 18 months later. At Nvidia GTC this week, five security vendors announced protection for Nvidia’s agentic AI stack, four with active deployments, one with validated early integration.

The timing reflects how fast the threat has moved: 48% of cybersecurity professionals rank agentic AI as the top attack vector heading into 2026. Only 29% of organizations feel fully ready to deploy these technologies securely. Machine identities outnumber human employees 82 to 1 in the average enterprise. And IBM’s 2026 X-Force Threat Intelligence Index documented a 44% surge in attacks exploiting public-facing applications, accelerated by AI-enabled vulnerability scanning.

Nvidia CEO Jensen Huang made the case from the GTC keynote stage on Monday: “Agentic systems in the corporate network can access sensitive information, execute code, and communicate externally. Obviously, this can’t possibly be allowed.”

Nvidia defined a unified threat model designed to flex and adapt for the unique strengths of five different vendors. Nvidia also names Google, Microsoft Security and TrendAI as Nvidia OpenShell security collaborators. This article maps the five vendors with embargoed GTC announcements and verifiable deployment commitments on record, an analyst-synthesized reference architecture, not Nvidia’s official canonical stack.

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No single vendor covers all five governance layers. Security leaders can evaluate CrowdStrike for agent decisions and identity, Palo Alto Networks for cloud runtime, JFrog for supply chain provenance, Cisco for prompt-layer inspection, and WWT for pre-production validation. The audit matrix below maps who covers what. Three or more unanswered vendor questions mean ungoverned agents in production.

The five-layer governance framework

This framework draws from the five vendor announcements and the OWASP Agentic Top 10. The left column is the governance layer. The right column is the question every security leader’s vendor should answer. If they can’t answer it, that layer is ungoverned.

Governance Layer

What To Deploy

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Risk If Not

Vendor Question

Who Maps Here

Agent Decisions

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Real-time guardrails on every prompt, response, and action

Poisoned input triggers privileged action

Detect state drift across sessions?

CrowdStrike Falcon AIDR, Cisco AI Defense [runtime enforcement]

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Local Execution

Behavioral monitoring for on-device agents

Local agent runs unprotected

Agent baselines beyond process monitoring?

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CrowdStrike Falcon Endpoint [runtime enforcement]; WWT ARMOR [pre-prod validation]

Cloud Ops

Runtime enforcement across cloud deployments

Agent-to-agent privilege escalation

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Trust policies between agents?

CrowdStrike Falcon Cloud Security [runtime enforcement]; Palo Alto Prisma AIRS [AI Factory validated design]

Identity

Scoped privileges per agent identity

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Inherited creds; delegation compounds

Privilege inheritance in delegation?

CrowdStrike Falcon Identity [runtime enforcement]; Palo Alto Networks/CyberArk [identity governance platform]

Supply Chain

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Model scanning + provenance before deploy

Compromised model hits production

Provenance from registry to runtime?

JFrog Agent Skills Registry [pre-deployment]; CrowdStrike Falcon

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Five-layer governance audit matrix. Three or more unanswered vendor questions indicate ungoverned agents in production. [runtime enforcement] = inline controls active during agent execution. [pre-deployment] = controls applied before artifacts reach runtime. [pre-prod validation] = proving-ground testing before production rollout. [AI Factory validated design] = Nvidia reference architecture integration, not OpenShell-launch coupling.

CrowdStrike’s Falcon platform embeds at four distinct enforcement points in the Nvidia OpenShell runtime: AIDR at the prompt-response-action layer, Falcon Endpoint on DGX Spark and DGX Station hosts, Falcon Cloud Security across AI-Q Blueprint deployments, and Falcon Identity for agent privilege boundaries. Palo Alto Networks enforces at the BlueField DPU hardware layer within Nvidia’s AI Factory validated design. JFrog governs the artifact supply chain from the registry through signing. WWT validates the full stack pre-production in a live environment. Cisco runs an independent guardrail at the prompt layer.

CrowdStrike and Nvidia are also building what they call intent-aware controls. That phrase matters. An agent constrained to certain data is access-controlled. An agent whose planning loop is monitored for behavioral drift is governed. Those are different security postures, and the gap between them is where the 4% error rate at 5x speed becomes dangerous.

Why the blast radius math changed

Daniel Bernard, CrowdStrike’s chief business officer, told VentureBeat in an exclusive interview what the blast radius of a compromised AI agent looks like compared to a compromised human credential.

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“Anything we could think about from a blast radius before is unbounded,” Bernard said. “The human attacker needs to sleep a couple of hours a day. In the agentic world, there’s no such thing as a workday. It’s work-always.”

That framing tracks with architectural reality. A human insider with stolen credentials works within biological limits: typing speed, attention span, a schedule. An AI agent with inherited credentials operates at compute speed across every API, database, and downstream agent it can reach. No fatigue. No shift change. CrowdStrike’s 2026 Global Threat Report puts the fastest observed eCrime breakout at 27 seconds and average breakout times at 29 minutes. An agentic adversary doesn’t have an average. It runs until you stop it.

When VentureBeat asked Bernard about the 96% accuracy number and what happens in the 4%, his answer was operational, not promotional: “Having the right kill switches and fail-safes so that if the wrong thing is decided, you’re able to quickly get to the right thing.” The implication is worth sitting on. 96% accuracy at 5x speed means the errors that get through arrive five times faster than they used to. The oversight architecture has to match the detection speed. Most SOCs are not designed for that.

Bernard’s broader prescription: “The opportunity for customers is to transform their SOCs from history museums into autonomous fighting machines.” Walk into the average enterprise SOC and inventory what’s running there. He’s not wrong.

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On analyst oversight when agents get it wrong, Bernard drew the governance line: “We want to keep not only agents in the loop, but also humans in the loop of the actions that the SOC is taking when that variance in what normal is realized. We’re on the same team.”

The full vendor stack

Each of the five vendors occupies a different enforcement point the other four do not. CrowdStrike’s architectural depth in the matrix reflects four announced OpenShell integration points; security leaders should weigh all five based on their existing tooling and threat model.

Cisco shipped Secure AI Factory with AI Defense, extending Hybrid Mesh Firewall enforcement to Nvidia BlueField DPUs and adding AI Defense guardrails to the OpenShell runtime. In multi-vendor deployments, Cisco AI Defense and Falcon AIDR run as parallel guardrails: AIDR enforcing inside the OpenShell sandbox, AI Defense enforcing at the network perimeter. A poisoned prompt that evades one still hits the other.

Palo Alto Networks runs Prisma AIRS on Nvidia BlueField DPUs as part of the Nvidia AI Factory validated design, offloading inspection to the data processing unit at the network hardware layer, below the hypervisor and outside the host OS kernel. This integration is best understood as a validated reference architecture pairing rather than a tight OpenShell runtime coupling. Palo Alto intercepts east-west agent traffic on the wire; CrowdStrike monitors agent process behavior inside the runtime. Same cloud runtime row, different integration model and maturity stage.

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JFrog announced the Agent Skills Registry, a system of record for MCP servers, models, agent skills, and agentic binary assets within Nvidia’s AI-Q architecture. Early integration with Nvidia has been validated, with full OpenShell support in active development. JFrog Artifactory will serve as a governed registry for AI skills, scanning, verifying, and signing every skill before agents can adopt it. This is the only pre-deployment enforcement point in the stack. As Chief Strategy Officer Gal Marder put it: “Just as a malicious software package can compromise an application, an unvetted skill can guide an agent to perform harmful actions.”

Worldwide Technology launched a Securing AI Lab inside its Advanced Technology Center, built on Nvidia AI factories and the Falcon platform. WWT’s vendor-agnostic ARMOR framework is a pre-production validation and proving-ground capability, not an inline runtime control. It validates how the integrated stack behaves in a live AI factory environment before any agent touches production data, surfacing control interactions, failure modes, and policy conflicts before they become incidents.

Three MDR numbers: what they actually measure

On the MDR side, CrowdStrike fine-tuned Nvidia Nemotron models on first-party threat data and operational SOC data from Falcon Complete engagements. Internal benchmarks show 5x faster investigations, 3x higher triage accuracy in high-confidence benign classification, and 96% accuracy in generating investigation queries within Falcon LogScale. Kroll, a global risk advisory and managed security firm that runs Falcon Complete as its MDR backbone, confirmed the results in production.

Because Kroll operates Falcon Complete as its core MDR platform rather than as a neutral third-party evaluator, their validation is operationally meaningful but not independent in the audit sense. Industry-wide third-party benchmarks for agentic SOC accuracy do not yet exist. Treat reported numbers as indicative, not audited.

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The 5x investigation speed compares average agentic investigation time (8.5 minutes) against the longest observed human investigation in CrowdStrike’s internal testing: a ceiling, not a mean. The 3x triage accuracy measures one internal model against another. The 96% accuracy applies specifically to generating Falcon LogScale investigation queries via natural language, not to overall threat detection or alert classification.

JFrog’s Agent Skills Registry operates beneath all four CrowdStrike enforcement layers, scanning, signing, and governing every model and skill before any agent can adopt it — with early Nvidia integration validated and full OpenShell support in active development.

Six enterprises are already in deployment

EY selected the CrowdStrike-Nvidia stack to power Agentic SOC services for global enterprises. Nebius ships with Falcon integrated into its AI cloud from day one. CoreWeave CISO Jim Higgins signed off on the Blueprint. Mondelēz North America Regional CISO Emmett Koen said the capability lets his team “focus on higher-value response and decision-making.”

MGM Resorts International CISO Bryan Green endorsed WWT’s validated testing environments, saying enterprises need “validated environments that embed protection from the start.” These range from vendor selection and platform validation to production integration. The signal is converging across buyer types, not uniform at-scale deployment.

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What the five-vendor stack does not cover

The governance framework above represents real progress. It also has three holes that every security leader deploying agentic AI will eventually hit. No vendor at GTC closed any of them. Knowing where they are is as important as knowing what shipped.

  1. Agent-to-agent trust. When agents delegate to other agents, credentials compound. The OWASP Top 10 for Agentic Applications lists tool call hijacking and orchestrator manipulation as top-tier risks. Independent research from BlueRock Security scanning over 7,000 MCP servers found 36.7% contain vulnerabilities. An arXiv preprint study across 847 scenarios found a 23 to 41% increase in attack success rates in MCP integrations versus non-MCP. No vendor at GTC demonstrated a complete trust policy framework for agent-to-agent delegation. This is the layer where the 82:1 identity ratio becomes a governance crisis, not just an inventory problem.

  2. Memory integrity. Agents with persistent memory create an attack surface that stateless LLM deployments do not have. Poison an agent’s long-term memory once. Influence its decisions weeks later. The OWASP Agentic Top 10 flags this explicitly. CrowdStrike’s intent-aware controls are the closest architectural response announced at GTC. Implementation details remain forward-looking.

  3. Registry-to-runtime provenance. JFrog’s Agent Skills Registry addresses the registry side of this problem. The gap that remains is the last mile: end-to-end provenance requires proving the model executing in production is the exact artifact scanned and signed in the registry. That cryptographic continuity from registry to runtime is still an engineering problem, not a solved capability.

What running five vendors actually costs

The governance matrix is a coverage map, not an implementation plan. Running five vendors across five enforcement layers introduces real operational overhead that the GTC announcements did not address. Someone has to own policy orchestration: deciding which vendor’s guardrail wins when AIDR and AI Defense return conflicting verdicts on the same prompt. Someone has to normalize telemetry across Falcon LogScale, Prisma AIRS, and JFrog Artifactory into a single incident workflow. And someone has to manage change control when one vendor ships a runtime update that shifts how another vendor’s enforcement layer behaves.

A realistic phased rollout looks like this: start with the supply chain layer (JFrog), because it operates pre-deployment and has no runtime dependencies on the other four. Add identity governance (Falcon Identity) second, because scoped agent credentials limit blast radius before you instrument the runtime. Then instrument the agent decision layer (Falcon AIDR or Cisco AI Defense, depending on your existing vendor footprint), then cloud runtime, then local execution. Running all five simultaneously from day one is an integration project, not a configuration task. Budget for it accordingly.

What to do before your next board meeting

Here is what every CISO should be able to say after running the framework above: “We have audited every autonomous agent against five governance layers. Here is what’s in place, and here are the five questions we are holding vendors to.” If you cannot say that today, the issue is not that you are behind schedule. The issue is that no schedule existed. Five vendors just shipped the architectural scaffolding for one.

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Do four things before your next board meeting:

  1. Run the five-layer audit. Pull every autonomous agent your organization has in production or staging. Map each one against the five governance rows above. Mark which vendor questions you can answer and which you cannot.

  2. Count the unanswered questions. Three or more means ungoverned agents in production. That is your board number, not a backlog item.

  3. Pressure-test the three open gaps. Ask your vendors, explicitly: How do you handle agent-to-agent trust across MCP delegation chains? How do you detect memory poisoning in persistent agent stores? Can you show a cryptographic binding between the registry scan and the runtime load? None of the five vendors at GTC has a complete answer. That is not an accusation. It is where the next year of agentic security gets built.

  4. Establish the oversight model before you scale. Bernard put it plainly: keep agents and humans in the loop. 96% accuracy at 5x speed means errors arrive faster than any SOC designed for human-speed detection can catch them. The kill switches and fail-safes have to be in place before the agents run at scale, not after the first missed breach.

The scaffolding is necessary. It is not sufficient. Whether it changes your posture depends on whether you treat the five-layer framework as a working instrument or skip past it in the vendor deck.

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MacBook Neo, MacBook Air, MacBook Pro: Which to buy in early 2026

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The MacBook lineup has finished its shift over to the M5 chip generation, and has been joined by the MacBook Neo. Here’s which model you should buy to fit your budget, as of early 2026.

Three open laptops with colorful abstract screens overlap in front of a faint background of U.S. dollar bills, suggesting technology purchases or laptop cost comparison.
MacBook Air [left], MacBook Neo [center], MacBook Pro [right]

Apple’s catalog of products is set up to provide consumers with both something that fits their budget, and an upgrade path that seems very close together. This ranges from a value-focused device like the new MacBook Neo to the bank-busting side with the MacBook Pro.
While this was previously a two-tier system, with the MacBook Air being the entry-level option, the introduction of the MacBook Neo changes things. We now have the entry-level Neo, with Air becoming the mid-tier choice, and the Pro line as the premium and performance option.
Continue Reading on AppleInsider | Discuss on our Forums

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IBM shows off quantum-centric supercomputing that merges processors and classical systems, hinting at scientific breakthroughs and future research applications

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  • IBM integrates quantum processors with classical supercomputers for coordinated scientific computations
  • Quantum-centric supercomputing allows workloads to switch between CPUs, GPUs, and QPUs
  • Researchers successfully simulated complex molecules using hybrid quantum-classical workflows

IBM has outlined a new reference architecture designed to combine quantum processors with traditional supercomputing infrastructure.

The company describes the concept as quantum-centric supercomputing, an approach intended to connect quantum processing units with GPUs and CPUs within large computing environments.

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The Forge Codes (March 2026)

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Update

Added new The Forge Codes on March 17, 2026.

The Forge is one of Roblox’s newer crafting-heavy RPGs, where players mine resources, forge weapons, and fight enemies while trying to obtain rare gear. As with most Roblox games, The Forge also has a healthy codes system that rewards players with free rerolls and other bonuses that help them improve their character faster. If you’re looking for the latest The Forge codes, you’ve come to the right place. Below, you’ll find all the working codes and instructions for redeeming them.

All New The Forge Codes

  • FORGEWEEKENDS — Redeem for 15x Rerolls  (NEW)

Codes in Roblox games tend to expire quickly, so make sure you redeem them as soon as possible before the developers remove them. Found an expired or missing code? Please let us know, and we’ll update the article as soon as possible.

Expired The Forge Codes

FREE15SPIN SORRYFORDELAYY CRIMSONSAKURA DELAYCOMPENSATION FORGEWEEKEND5
MAZE! FORGWEEKEND! RAVEN HAPPYNEWYEAR FORGE2M
FORG! FREESPINS PEAK! 400K! SORRYFORSHUTDOWN
40KLIKES 20KLIKES 15KLIKES 10KLIKES 5KLIKES

How to Redeem The Forge Codes?

Redeeming codes in The Forge is quick and easy. Just follow these steps:

  1. Open The Forge in Roblox.
  2. Click on the Settings button at the top.
    An arrow pointing to the settings button in The Forge to redeem codes
  3. Scroll to the Codes section.
  4. Type your desired code and hit Redeem.Section to type The Forge codes

That’s it. Your rewards will be automatically added to your inventory. In the meantime, check out the codes for Steal a Brainrot, Uma Racing, and Funky Friday.

Why Are My The Forge Codes Not Working?

There can be plenty of reasons why your code isn’t working, chief among them being that the code has expired. We are not robots, and these articles are maintained by humans, who only work certain hours of the day. Since many Roblox codes only last a short time, it’s possible that a code expired between the time of writing this article and when you tried to redeem it.

Beyond that, it’s possible you’ve typed the code wrong. They are case-sensitive, meaning even a small spelling error will cause them to fail. So, double-check your spelling, or simply copy and paste from the article. Sometimes new codes appear after updates, but they may take a few minutes to activate across servers. If that happens, try restarting the game and redeeming the code again.

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How to Get More The Forge Codes?

Discord invite section of The Forge

The easiest way to find new The Forge codes is to bookmark this page. We regularly check for updates and add new codes as soon as they appear. You can also join the official The Forge Discord server, where the developers usually post announcements and new codes first. The dedicated codes channel is the best place to watch for future rewards.

Developers usually release new codes when a game reaches major milestones, such as a high player count, new updates, bug fixes, and seasonal events or holidays. So, we recommend keeping an eye out for these.

What Is The Forge in Roblox?

A character from The Forge forging a weapon

For those new to the game, The Forge is a crafting-focused RPG on Roblox where players mine resources, forge weapons, and fight enemies to obtain rare items. Unlike many other Roblox RPGs, the game puts heavy emphasis on crafting mechanics. Players can create their own equipment using mined materials and enhance their builds through race rerolls and powerful items. Because of this system, The Forge codes are extremely helpful early in the game since rerolls can significantly change your build.

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Microsoft revamps Copilot structure, elevating former Snap exec as Suleyman shifts to AI models

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Mustafa Suleyman, CEO of Microsoft AI, will shift his focus to building frontier AI models and leading the company’s superintelligence efforts under a reorganization announced Tuesday. (GeekWire File Photo / Kevin Lisota)

Microsoft is reorganizing its Copilot organization, unifying its consumer and commercial AI efforts under former Snap executive Jacob Andreou while narrowing the role of Microsoft AI leader Mustafa Suleyman to focus on the superintelligence and frontier models.

The news, announced Tuesday by Microsoft CEO Satya Nadella, is a new attempt by the company to gain traction as AI shifts from chatbots that converse with users to agents that take action on their behalf. It’s the latest shakeup in the company’s executive ranks. 

Microsoft 365 Copilot had 15 million paying users at last count, about 3% of the overall user base for the enterprise platform. Estimates from Statcounter show Copilot with a low‑single‑digit share of global AI chatbot usage, well behind its partner OpenAI’s ChatGPT.

“This is how we move from a collection of great products to a truly integrated system, one that is simpler and more powerful for customers,” Nadella said in an email to employees about the changes, published by the company on its website.

Andreou joined Microsoft last year from Snap, where he spent eight years and rose to senior vice president. As corporate vice president of product and growth at Microsoft AI, he has been leading the consumer Copilot effort. As executive vice president of the combined Copilot group, he will report directly to Nadella, leading overall design, product, growth, and engineering.

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Suleyman, a co-founder of DeepMind, joined Microsoft as CEO of AI when the company brought over most of the team from his AI startup Inflection AI in 2024.  He will continue reporting to Nadella but shift his focus to building frontier AI models. 

Microsoft formed a Superintelligence team under Suleyman in November, and Tuesday’s restructuring effectively makes that his primary mandate.

In his email to staff, Suleyman said the restructuring will allow him to commit fully to the company’s superintelligence efforts and deliver models over the next five years that improve products and reduce the cost of running AI workloads at scale.

Microsoft 365 apps and the Copilot platform will be led by Ryan Roslansky, CEO of LinkedIn; Perry Clarke, who leads Microsoft 365 core infrastructure; and Charles Lamanna, who oversees business and industry Copilot. Together with Andreou and Suleyman, they will form a new Copilot Leadership Team.  

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Roslansky, Clarke and Lamanna began reporting directly to Nadella earlier this month as part of the succession plan for Rajesh Jha, the longtime executive vice president who is retiring after more than 35 years at the company.

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DOGE Didn’t Cut Government Waste. It Was Government Waste.

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from the a-failure-at-any-level dept

Look, I get it. Government waste is real. Bureaucratic bloat is real. The desire to have a federal government that spends taxpayer money wisely and operates without unnecessary friction? That’s a pretty standard and quite reasonable desire in American politics. So when Elon Musk showed up promising he could cut $2 trillion in federal spending by bringing the vaunted “efficiency” of the tech world to the government, a lot of people — not just MAGA diehards, but regular people who’d spent time cursing at a federal website built in 2003 or waiting on hold with the DMV — thought: sure, maybe give it a shot. A decade of fawning tech press coverage about Elon Musk will do that to your priors.

We now have the receipts on how that went. And they’re absolutely damning.

Between a comprehensive forensic accounting from the New York Times published in December and a detailed report from House Oversight Committee Ranking Member Robert Garcia released in February, we can now do a proper post-mortem on DOGE. The diagnosis: the patient was dead on arrival, the surgery was performed by people who lied about their credentials, and the bill for the operation far exceeded anything that was supposedly “saved.”

Let’s start with the most basic question: did DOGE save the government money? Because that was, you know, apparently the whole point (or so we were told).

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The answer, as the Times bluntly puts it:

But the group did not do what Mr. Musk said it would: reduce federal spending by $1 trillion before October. On DOGE’s watch, federal spending did not go down at all. It went up.

Spending went up. Musk promised $2 trillion in cuts during the campaign, started walking that back almost immediately after the election, and the actual result was that the government spent more money. The entire exercise was supposed to pay for itself many times over. Instead, the taxpayer funded an $81 million operation that produced negative returns.

But DOGE had that website — the “Wall of Receipts” — proudly tallying up all those billions in savings, right? About that. The Times went through the 40 largest items on DOGE’s claimed savings list:

In DOGE’s published list of canceled contracts and grants, for instance, the 13 largest were all incorrect.

At the top were two Defense Department contracts, one for information technology, one for aircraft maintenance. Mr. Musk’s group listed them as “terminations,” and said their demise had saved taxpayers $7.9 billion. That was not true. The contracts are still alive and well, and those savings were an accounting mirage.

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Together, those two false entries were bigger than 25,000 of DOGE’s other claims combined.

Of the 40 biggest claims on DOGE’s list, The Times found only 12 that appeared accurate — reflecting real reductions in what the government had committed to spend.

Two fake line items on a spreadsheet claimed more “savings” than 25,000 other entries combined. Of the 40 biggest claims, 28 were wrong. The 13 biggest were all wrong. The very first day the “Wall of Receipts” went live, its largest claim was an $8 billion Department of Homeland Security contract that was off by a factor of 1,000 — the contract was actually worth $8 million, as many folks reported at the time. That’s the kind of error that would get you fired from an introductory accounting course, and these were the people supposedly bringing precision and transparency to the federal government.

The accounting trick DOGE relied on most heavily is worth understanding, because it reveals whether this was mere incompetence or something more deliberate. The Times explains that in many cases, DOGE simply lowered the “ceiling value” of contracts — the theoretical maximum the government could spend, not what it was actually spending — and then claimed the full difference as “savings.” A defense contractor CEO explained this perfectly to stock analysts:

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This summer, CACI’s chief executive, John Mengucci, told stock analysts that the change was meaningless.

“It doesn’t change a thing for this company,” he said. His company had always expected to be paid about $2 billion over the contract’s life span. And even if the contract ever did reach the ceiling, he said, the Pentagon could just raise it again.

“There’s no reduction of revenue,” Mr. Mengucci said.

Or to put it in even more understandable terms:

“Does lowering the maximum limit on your credit card save you any money?” said Travis Sharp, a senior fellow at the Center for Strategic and Budgetary Assessments, which studies federal spending. “No, it does not.”

The core of DOGE’s operations was to manufacture pretend statistics so that Musk and friends could claim savings that weren’t real. It was how DOGE manufactured the appearance of progress while delivering essentially nothing. After DOGE initially claimed $55 billion in savings, the website’s own documentation only supported $16.5 billion. Media analysis then showed half of that was a single data entry error (that $8 billion instead of $8 million). A Politico analysis found DOGE had cut only $1.4 billion in actual spending — and even that money couldn’t reduce the deficit because it would be returned to agencies that were legally obligated to spend it. More than one-third of DOGE’s contract cancellations yielded no monetary savings at all.

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The Garcia report traces a trajectory that any honest observer should find embarrassing:

During the 2024 presidential campaign, Elon Musk claimed he could reduce the federal deficit by eliminating “at least $2 trillion” in federal spending, promising the destruction of the American social safety net. He began walking back these goals after President Trump’s election victory. In early 2025, Mr. Musk appeared on a variety of conservative-leaning podcasts and media outlets baselessly claiming that fake or stolen Social Security numbers led to more than $500 billion in fraud. Media analysis classified Mr. Musk’s claims about waste and fraud in the federal government as lacking evidence or misleading, saying that he misconstrued Government Accountability Office (GAO) reports or lacked basic understanding of the contracts in question.

So: $2 trillion, then $1 trillion, then $55 billion claimed, then $16.5 billion documented, then $1.4 billion confirmed, then spending went up anyway. That’s quite a trajectory for something that was sold as bringing Silicon Valley precision and efficiency to government.

Okay, fine — DOGE didn’t save much money. But did it at least make the government run better? Did it cut red tape, speed things up, make services less awful?

No. It did the opposite. And this is the part that should really bother anyone who genuinely wanted government reform.

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The Garcia report documents in excruciating detail how DOGE’s “efficiency” measures actually added bureaucratic layers:

In one example, a State Department employee described a new requirement for a 250-word essay, extra forms, and days of work and approvals needed to hire a vendor for an embassy event, which previously would have taken a single day. In another, a NASA employee was required to write several detailed paragraphs justifying a purchase of fastening bolts. FDA employees have stated that DOGE requirements have caused significant delays in routine food monitoring tests for items like exposure to heavy metals because spending for every step—from purchasing lab supplies to paying to ship samples between labs—now requires separate department-level approval.

Much efficient. Very savings.

As one federal employee stated:

“It is becoming increasingly difficult to continue to work, which I fear is the point.”

Meanwhile, the services Americans actually rely on got measurably worse:

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At the Social Security Administration (SSA), wait times for a callback ballooned to as high as two and a half hours for assistance between January and March 2025. Americans attempting to access the SSA website for assistance frequently found the webpage down or unresponsive as DOGE recklessly implemented changes while cutting information technology (IT) staff. SSA eventually discarded several of the supposed fraud checks implemented by DOGE because they significantly delayed claim processing without meaningfully combatting fraud. Career employees reportedly knew that DOGE’s anti-fraud measures would make little difference but were intimidated into silence for fear of losing their jobs. DOGE also implemented a new requirement for Social Security applicants to verify their identity in person instead of over the phone if they aren’t able to do so online, while at the same time closing regional and local offices and reducing the workforce at those offices that remained. More than six million seniors have to drive nearly 50 miles round trip to reach their nearest Social Security office, more than twice the average distance an elderly person expects to drive in a day.

This was a heist dressed up as a reform — and the damage to everyday Americans wasn’t a bug.

Layoffs at the Food and Drug Administration (FDA) led to delays in clinical trials and getting new drugs to sick patients. Remaining FDA workers reported struggling to meet statutorily mandated schedules for approving both tobacco products and medical products after the Trump Administration announced 3,500 job cuts across the agency. At one point, FDA drug center leadership resorted to asking drug review staff to volunteer to work on contracting and acquisition tasks because the layoffs had eliminated the entire contracting office.

The Times talked to people on the receiving end of the small-dollar cuts that were DOGE’s actual handiwork. An organization providing counseling and rehabilitation services to torture survivors had to close its centers and stop paying 75% of its staff. A program that sent museum staff into low-income Baltimore schools to teach parents about child development was terminated by form letter because it “no longer serves the interest of the United States.” Research projects were killed at the stage where data had been collected but results hadn’t been published, rendering the government’s entire prior investment wasted. And the impact on American people was real.

Mr. Roehm said he was particularly concerned about possible suicides — around a quarter of the torture victims the group served had recently experienced suicidal ideation.

“We know for sure that survivors we are no longer able to serve are suffering,” he said.

Those dollar amounts were small, compared with DOGE’s largest claims. That is, in effect, how DOGE ultimately saved so little but still caused so much disruption. For small business and local communities, relatively modest sums had major effects.

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“It’s the small numbers that hurt people,” said Lisa Shea Mundt, whose company, the Pulse of GovCon, tracks government contracts.

This is how DOGE managed to simultaneously save almost nothing and cause enormous disruption: the big-dollar claims were fake, and the real cuts targeted things that were individually small but collectively devastating to the people who depended on them.

And then there’s the corruption angle, which is where this moves from incompetence into something much uglier.

DOGE staff were embedded at nearly every executive branch agency, and many of them were associates or employees of Musk’s own companies. The conflicts of interest were staggering and barely concealed. The Garcia report details how DOGE staff were involved in firing FDA investigators responsible for oversight of Musk’s biotech company Neuralink. DOGE took aim at the Consumer Financial Protection Bureau — which just happened to be the agency that would directly oversee a mobile payments function Musk wanted to add to X. The DOGE staffer who oversaw firings at the CFPB owned approximately $365,000 in shares of companies regulated by the Bureau. Executive branch employees are generally prohibited from working on matters in which they hold a personal stake, but there’s no indication this person took any such precautions.

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Elon Musk and DOGE’s active involvement in knee-capping agencies with which he has a direct conflict makes clear that Musk, DOGE, and the broader Trump Administration are focused on weakening accountability for the American people while advancing their own interests.

DOGE staff at the IRS initiated mass firing of skilled specialists responsible for auditing the complex tax filings of large corporations and the ultra-wealthy. The Congressional Budget Office has found that reductions in funding for IRS tax enforcement reduce federal revenues. So DOGE’s “efficiency” move at the IRS will likely cost the government more in uncollected taxes than it could ever have saved.

The same pattern held at the CFPB, which since 2011 had received $7.3 billion in funding but returned over $21 billion to consumers through enforcement actions — a three-fold return on investment. DOGE gutted it anyway. The IRS Direct File program — a free electronic tax filing service that 86% of users said increased their trust in the IRS and was projected to save taxpayers $11 billion once fully operational — was killed after lobbying by for-profit tax preparation companies.

And perhaps most alarming were the data security violations that I’ve written about multiple times. A whistleblower from SSA reported that DOGE operatives had accessed a database containing “the entire country’s Social Security information,” copied it to a high-risk external system, and violated a court order barring them from continued access. The DOJ later had to file “corrections” to prior testimony from senior SSA staff, admitting that DOGE employees had in fact accessed SSA’s most sensitive data and covertly signed a “Voter Data Agreement” with a political advocacy group that sought to overturn election results. And here’s one I had missed:

DOGE’s forced access to Treasury data was particularly noteworthy as a Treasury threat intelligence analysis recommended that DOGE staff “be placed under insider threat monitoring and alerting after their access to payment systems is revoked. Continued access to any payment systems by DOGE members, even ‘read only,’ may have posed the single greatest insider threat risk the Bureau of the Fiscal Service has ever faced.”

At the NLRB, a whistleblower reported that DOGE operatives sent enormous amounts of sensitive case information outside the government to unknown recipients — information that companies like Musk’s SpaceX could use to “get insights into damaging testimony, union leadership, legal strategies and internal data.” OPM’s own Inspector General found that DOGE employees flouted cybersecurity and privacy laws, and that Trump appointees at OPM overrode career civil servants’ warnings about security to force implementation of DOGE’s systems, which may have resulted in a massive national security threat:

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Experts have shown evidence raising concerns of potential Russian and Chinese access to OPM servers shortly after DOGE created the government-wide email infrastructure. Separately, information received by Committee Democratic staff indicated that DOGE employees lowered all firewall protections at OPM to enable the exfiltration of data for use outside of a government environment.

Yikes.

And while they were gutting agencies that protect Americans, they also gutted the agencies actually responsible for catching waste, fraud, and abuse. Offices of Inspectors General — the very watchdogs whose mission aligns with what DOGE claimed to be doing — were starved of resources. One OIG lost 20% of its staff and was operating with “the fewest number of auditors in decades.” The DOJ’s Public Integrity Section, which oversees prosecutions of politicians accused of corruption, was purged of all but a fraction of its former employees.

The Garcia report’s conclusion is perhaps the most honest assessment of the whole debacle:

Many analyses have referred to the DOGE disaster as a failure, and DOGE did indeed fail at its stated mission of meaningfully reducing spending and increasing government efficiency. But in the Trump Administration’s vindictive, ideologically motivated, and pointless quest to break the federal government, drive out talented and committed public servants, and make flashy promises of cutting fraud while enriching themselves and their wealthy donors, DOGE was a resounding success.

Now, the Garcia report is a Democratic minority report, and the most committed DOGE defenders will dismiss it on those grounds alone. But the most devastating evidence comes from DOGE’s own website — which kept quietly deleting incorrect entries — from the Times’ independent analysis, from a defense contractor’s CEO telling his shareholders the “savings” were meaningless, from the GAO finding multiple violations of the Impoundment Control Act, from OPM’s own Inspector General, and from the DOJ having to file corrections to its own court filings.

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You don’t need to trust a single Democratic politician to see what happened here. You just need to look at the numbers.

Oh, and yes: Musk himself admitted in a podcast interview with MAGA influencer and former DOGE employee Katie Miller (wife of Stephen) in December that DOGE had fallen short and said that if he could go back in time, he wouldn’t do it again, preferring instead to have “worked on my companies.” The man who was going to supposedly save the republic from government bloat decided his actual companies were more worth his time. Musk’s public admission probably shouldn’t carry too much weight either way — he knows DOGE was publicly perceived as a failure and he’s distancing himself — but it is a fitting coda.

This whole thing was billed not just by MAGA faithful, but also by many in the media, as an expected triumph of private sector brilliance over government incompetence. What it actually demonstrated is that when you hand the keys to people who don’t understand how government works, don’t respect the people who do, and have massive personal financial conflicts of interest, you get chaos, corruption, and a bigger bill for taxpayers. The people who were making government work better — the original U.S. Digital Service employees who were building more efficient systems and better websites — got fired and replaced with Musk acolytes who couldn’t tell the difference between a contract ceiling and actual spending.

The MAGA world continues to pretend DOGE was a ruthless cost-cutting machine. The receipts say otherwise: it failed in every direction except enriching corporations connected to the administration. It was a looting operation dressed up as reform.

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Filed Under: abuse, doge, efficiency, elon musk, fraud, government spending, waste

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Are Split Spacebars the Next Big Gaming Keyboard Trend?

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“There are countless upgrades you could make to your gaming setup,” writes PC Gamer’s Jacob Ridley. “A wireless this, a bigger that, a faster thing. But how do you know what’s going to be a genuine upgrade worth investing in? Personally, I think it might be split spacebars.” His argument centers on the fact that spacebars take up a “greedy” amount of keyboard space — space that could instead be divided into multiple keys for different actions, such as voice chat or melee attacks. From the report: While it’s often very easy to reprogram your spacebar to do a different action via your keyboard’s software, it’s a lot harder to reprogram your brain to hit any other key when you try to jump in game. Spacebar makes you jump. Everyone knows that; it’s practically etched onto your brain if you’re a long-time mouse and keyboard player. So, why does a split spacebar help with that? It comes down to this: once you know which side of a spacebar you tend to thwack with your thumb, you can program the other side to do whatever you want. I hit the right-side of my spacebar every time when I’m typing. Therefore, when I started using a Wooting 60HE v2 with a split spacebar, I set the left-side to be the delete key; the keyboard lacking a dedicated delete key for its 60% size.

Though for gaming, the split spacebar offers much more varied purpose. People do strange things with the WASD keys that I won’t litigate here, but I’m pretty sure most gamers use their left thumb to strike the spacebar for gaming. Right? Right. If you fall into this category, you have the option of using the right-side spacebar for things like a chunky melee key, or, my personal favorite, an in-game voice chat key.

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This Is JD Power’s Most Satisfying Place To Buy Home Appliances

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It’s safe to assume that brand name tops the list for many people in the market for a new refrigerator, stove, or washing machine. If, however, you’re struggling to decide on the brand, consumer ratings companies like JD Power may prove an invaluable source of information, as they regularly assemble lists for categories like brand reliability and, of course, customer satisfaction.

JD Power’s 2025 U.S. Appliance Satisfaction Study confirms that many of the major home appliance manufacturers, including Samsung, LG, and GE, are indeed the best currently available in the market. JD Power’s data doesn’t stop there, though, and reading the study report all the way through reveals that it also offers some welcome insight into which appliance retailer offers the most satisfying experience for buyers.

Despite what you might expect, Lowe’s did not earn the top spot in that sector of the study. Rather, that honor went to one of the big box home improvement chain’s primary competitors, The Home Depot. The retailer claimed top spot with a customer satisfaction score of 700 points out of 1,000. According to JD Power, those numbers are based on 15,884 evaluations collected from consumers who purchased a new appliance over 12 months between 2024 and 2025. Per the outlet, the place of purchase was one of 12 different categories included in the survey.

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Lowe’s didn’t make the Top 3 in JD Power’s appliance study

If you’re a Lowe’s fan and wondering how it performed in JD Power’s study, you might be disappointed to learn that the outfit wasn’t even in the top 3 most satisfying retailers. After The Home Depot, survey respondents also claimed that Best Buy left them feeling better than most after their new appliance purchase, with the national electronics chain coming in second with a score of 689 out of 1,000.

For the record, that Best Buy score was just above the segment average of 683, with The Home Depot and Best Buy serving as the only two major retailers that performed better than average. Third place went to Menards, with the family-owned Midwest staple earning a just below average score of 674 out of 1,000. As for Lowe’s, the retailer at least managed to place in the top 5, ultimately slotting into fourth place with a score of 673 points out of 1,000.

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Costco is next up on the list, with the popular wholesale chain scoring 657 points. Occupying the final spot on JD Power’s customer satisfaction study is P.C. Richard & Son. It looks to be the smallest national chain on the list, though the company has been around in some capacity for more than 100 years. Its customer satisfaction numbers are pretty respectable too, with the retailer’s 614 points allowing it to claim sixth in JD Power’s 2025 study. 



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WhatsApp is now officially available on Garmin smartwatches

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There’s an official WhatsApp app . It’s available for free right now in the Garmin Connect IQ Store. WhatsApp is primarily a chat platform, so this new app allows users to read and reply to messages, send emojis and peruse the chat history.

The app also lets users accept or decline incoming calls arriving from the platform, all without having to break out the smartphone. This is WhatsApp, so messages are end-to-end encrypted.

As previously mentioned, it’s not available for every Garmin watch. It’s compatible with select Forerunner, Venu, Vivoactive and Fenix watches. The Connect IQ Store should be able to say if your particular model can handle the app.

This is just the latest smartwatch platform to get WhatsApp. Meta released an at the tail-end of last year. Before that, Apple Watch users had to mirror iPhone notifications to reply to WhatsApp messages directly from the device.

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