Traditional software governance often uses static compliance checklists, quarterly audits and after-the-fact reviews. But this method can’t keep up with AI systems that change in real time. A machine learning (ML) model might retrain or drift between quarterly operational syncs. This means that, by the time an issue is discovered, hundreds of bad decisions could already have been made. This can be almost impossible to untangle.
In the fast-paced world of AI, governance must be inline, not an after-the-fact compliance review. In other words, organizations must adopt what I call an “audit loop”: A continuous, integrated compliance process that operates in real-time alongside AI development and deployment, without halting innovation.
This article explains how to implement such continuous AI compliance through shadow mode rollouts, drift and misuse monitoring and audit logs engineered for direct legal defensibility.
From reactive checks to an inline “audit loop”
When systems moved at the speed of people, it made sense to do compliance checks every so often. But AI doesn’t wait for the next review meeting. The change to an inline audit loop means audits will no longer occur just once in a while; they happen all the time. Compliance and risk management should be “baked in” to the AI lifecycle from development to production, rather than just post-deployment. This means establishing live metrics and guardrails that monitor AI behavior as it occurs and raise red flags as soon as something seems off.
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For instance, teams can set up drift detectors that automatically alert when a model’s predictions go off course from the training distribution, or when confidence scores fall below acceptable levels. Governance is no longer just a set of quarterly snapshots; it’s a streaming process with alerts that go off in real time when a system goes outside of its defined confidence bands.
Cultural shift is equally important: Compliance teams must act less like after-the-fact auditors and more like AI co-pilots. In practice, this might mean compliance and AI engineers working together to define policy guardrails and continuously monitor key indicators. With the right tools and mindset, real-time AI governance can “nudge” and intervene early, helping teams course-correct without slowing down innovation.
In fact, when done well, continuous governance builds trust rather than friction, providing shared visibility into AI operations for both builders and regulators, instead of unpleasant surprises after deployment. The following strategies illustrate how to achieve this balance.
Shadow mode rollouts: Testing compliance safely
One effective framework for continuous AI compliance is “shadow mode” deployments with new models or agent features. This means a new AI system is deployed in parallel with the existing system, receiving real production inputs but not influencing real decisions or user-facing outputs. The legacy model or process continues to handle decisions, while the new AI’s outputs are captured only for analysis. This provides a safe sandbox to vet the AI’s behavior under real conditions.
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According to global law firm Morgan Lewis: “Shadow-mode operation requires the AI to run in parallel without influencing live decisions until its performance is validated,” giving organizations a safe environment to test changes.
Teams can discover problems early by comparing the shadow model’s decisions to expectations (the current model’s decisions). For instance, when a model is running in shadow mode, they can check to see if its inputs and predictions differ from those of the current production model or the patterns seen in training. Sudden changes could indicate bugs in the data pipeline, unexpected bias or drops in performance.
In short, shadow mode is a way to check compliance in real time: It ensures that the model handles inputs correctly and meets policy standards (accuracy, fairness) before it is fully released. One AI security framework showed how this method worked: Teams first ran AI in shadow mode (AI makes suggestions but doesn’t act on its own), then compared AI and human inputs to determine trust. They only let the AI suggest actions with human approval after it was reliable.
For instance, Prophet Security eventually let the AI make low-risk decisions on its own. Using phased rollouts gives people confidence that an AI system meets requirements and works as expected, without putting production or customers at risk during testing.
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Real-time drift and misuse detection
Even after an AI model is fully deployed, the compliance job is never “done.” Over time, AI systems can drift, meaning that their performance or outputs change due to new data patterns, model retraining or bad inputs. They can also be misused or lead to results that go against policy (for example, inappropriate content or biased decisions) in unexpected ways.
To remain compliant, teams must set up monitoring signals and processes to catch these issues as they happen. In SLA monitoring, they may only check for uptime or latency. In AI monitoring, however, the system must be able to tell when outputs are not what they should be. For example, if a model suddenly starts giving biased or harmful results. This means setting “confidence bands” or quantitative limits for how a model should behave and setting automatic alerts when those limits are crossed.
Some signals to monitor include:
Data or concept drift: When input data distributions change significantly or model predictions diverge from training-time patterns. For example, a model’s accuracy on certain segments might drop as the incoming data shifts, a sign to investigate and possibly retrain.
Anomalous or harmful outputs: When outputs trigger policy violations or ethical red flags. An AI content filter might flag if a generative model produces disallowed content, or a bias monitor might detect if decisions for a protected group begin to skew negatively. Contracts for AI services now often require vendors to detect and address such noncompliant results promptly.
User misuse patterns: When unusual usage behavior suggests someone is trying to manipulate or misuse the AI. For instance, rapid-fire queries attempting prompt injection or adversarial inputs could be automatically flagged by the system’s telemetry as potential misuse.
When a drift or misuse signal crosses a critical threshold, the system should support “intelligent escalation” rather than waiting for a quarterly review. In practice, this could mean triggering an automated mitigation or immediately alerting a human overseer. Leading organizations build in fail-safes like kill-switches, or the ability to suspend an AI’s actions the moment it behaves unpredictably or unsafely.
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For example, a service contract might allow a company to instantly pause an AI agent if it’s outputting suspect results, even if the AI provider hasn’t acknowledged a problem. Likewise, teams should have playbooks for rapid model rollback or retraining windows: If drift or errors are detected, there’s a plan to retrain the model (or revert to a safe state) within a defined timeframe. This kind of agile response is crucial; it recognizes that AI behavior may drift or degrade in ways that cannot be fixed with a simple patch, so swift retraining or tuning is part of the compliance loop.
By continuously monitoring and reacting to drift and misuse signals, companies transform compliance from a periodic audit to an ongoing safety net. Issues are caught and addressed in hours or days, not months. The AI stays within acceptable bounds, and governance keeps pace with the AI’s own learning and adaptation, rather than trailing behind it. This not only protects users and stakeholders; it gives regulators and executives peace of mind that the AI is under constant watchful oversight, even as it evolves.
Audit logs designed for legal defensibility
Continuous compliance also means continuously documenting what your AI is doing and why. Robust audit logs demonstrate compliance, both for internal accountability and external legal defensibility. However, logging for AI requires more than simplistic logs. Imagine an auditor or regulator asking: “Why did the AI make this decision, and did it follow approved policy?” Your logs should be able to answer that.
A good AI audit log keeps a permanent, detailed record of every important action and decision AI makes, along with the reasons and context. Legal experts say these logs “provide detailed, unchangeable records of AI system actions with exact timestamps and written reasons for decisions.” They are important evidence in court. This means that every important inference, suggestion or independent action taken by AI should be recorded with metadata, such as timestamps, the model/version used, the input received, the output produced and (if possible) the reasoning or confidence behind that output.
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Modern compliance platforms stress logging not only the result (“X action taken”) but also the rationale (“X action taken because conditions Y and Z were met according to policy”). These enhanced logs let an auditor see, for example, not just that an AI approved a user’s access, but that it was approved “based on continuous usage and alignment with the user’s peer group,” according to Attorney Aaron Hall.
Audit logs should also be well-organized and difficult to change if they are to be legally sound. Techniques like immutable storage or cryptographic hashing of logs ensure that records can’t be changed. Log data should be protected by access controls and encryption so that sensitive information, such as security keys and personal data, is hidden or protected while still being open.
In regulated industries, keeping these logs can show examiners that you are not only keeping track of AI’s outputs, but you are retaining records for review. Regulators are expecting companies to show more than that an AI was checked before it was released. They want to see that it is being monitored continuously and there is a forensic trail to analyze its behavior over time. This evidentiary backbone comes from complete audit trails that include data inputs, model versions and decision outputs. They make AI less of a “black box” and more of a system that can be tracked and held accountable.
If there is a disagreement or an event (for example, an AI made a biased choice that hurt a customer), these logs are your legal lifeline. They help you figure out what went wrong. Was it a problem with the data, a model drift or misuse? Who was in charge of the process? Did we stick to the rules we set?
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Well-kept AI audit logs show that the company did its homework and had controls in place. This not only lowers the risk of legal problems but makes people more trusting of AI systems. With AI, teams and executives can be sure that every decision made is safe because it is open and accountable.
Inline governance as an enabler, not a roadblock
Implementing an “audit loop” of continuous AI compliance might sound like extra work, but in reality, it enables faster and safer AI delivery. By integrating governance into each stage of the AI lifecycle, from shadow mode trial runs to real-time monitoring to immutable logging, organizations can move quickly and responsibly. Issues are caught early, so they don’t snowball into major failures that require project-halting fixes later. Developers and data scientists can iterate on models without endless back-and-forth with compliance reviewers, because many compliance checks are automated and happen in parallel.
Rather than slowing down delivery, this approach often accelerates it: Teams spend less time on reactive damage control or lengthy audits, and more time on innovation because they are confident that compliance is under control in the background.
There are bigger benefits to continuous AI compliance, too. It gives end-users, business leaders and regulators a reason to believe that AI systems are being handled responsibly. When every AI decision is clearly recorded, watched and checked for quality, stakeholders are much more likely to accept AI solutions. This trust benefits the whole industry and society, not just individual businesses.
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An audit-loop governance model can stop AI failures and ensure AI behavior is in line with moral and legal standards. In fact, strong AI governance benefits the economy and the public because it encourages innovation and protection. It can unlock AI’s potential in important areas like finance, healthcare and infrastructure without putting safety or values at risk. As national and international standards for AI change quickly, U.S. companies that set a good example by always following the rules are at the forefront of trustworthy AI.
People say that if your AI governance isn’t keeping up with your AI, it’s not really governance; it’s “archaeology.” Forward-thinking companies are realizing this and adopting audit loops. By doing so, they not only avoid problems but make compliance a competitive advantage, ensuring that faster delivery and better oversight go hand in hand.
Dhyey Mavani is working to accelerate gen AI and computational mathematics.
Editor’s note: The opinions expressed in this article are the authors’ personal opinions and do not reflect the opinions of their employers.
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The OPPO F-series has always focused on the durability side of things, with some of the toughest phones I’ve ever tested. With the new F33 series, the Chinese smartphone maker is bringing a new type of durability-focused smartphone to India. Based on details shared ahead of launch, the company is positioning the lineup as a solution to everyday smartphone problems like cracked screens, water damage, and battery anxiety.
Built for Indian Conditions
Durability seems to be the core focus here. The OPPO F33 series is said to come with IP69K certification, which is a step above the usual IP67 or IP68 ratings seen in most mid-range phones. In practical terms, this means the device can handle high-pressure, high-temperature water jets and provide complete dust protection. It’s designed to survive not just accidental splashes, but harsher environments like heavy rain, kitchens, or dusty outdoor conditions.
Beyond certifications, OPPO says the F33 series has undergone military-grade durability testing. This includes extreme temperature tests ranging from freezing cold to high heat, salt exposure for coastal conditions, and even simulations of strong winds and heavy rainfall. The devices are also tested for drops, with thousands of simulated falls and immersion tests to ensure real-world reliability.
Structurally, the phones feature a 360-degree armor body, built using an aerospace-grade aluminium frame, reinforced internals, and thicker protective materials for both the display and back panel. There’s also an internal cushioning system designed to absorb shocks during impact.
Long-Term Battery Health
Battery life is another major highlight of the F33 series. OPPO is introducing a 7,000mAh battery that’s designed to retain up to 80% of its capacity even after five years of usage.
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The company is using a self-repairing electrolyte technology, which is said to help maintain battery health over time. Combined with 80W fast charging, reverse charging, and bypass charging support, the F33 series aims to reduce both charging time and long-term battery degradation.
The nonprofit organisation will remain active on other social media platforms.
The prominent digital rights nonprofit Electronic Frontier Foundation (EFF) will no longer use social media platform X, primarily due to diminishing engagement from its posts there.
In a blogpost explaining its decision, the EFF said that “an X post today receives less than 3pc of the views a single tweet delivered seven years ago”.
Earlier this week, the Harvard-based NiemanLab published an “analysis of thousands of tweets from 18 publishers” suggesting that linked posts on X are not driving significant traffic to their sites.
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The social media network formerly known as Twitter was acquired by Elon Musk in October 2022 before setting about removing restrictions, oversight and moderation of content.
The EFF said that at the time of the takeover, its priorities for improvement of the platform were transparent content moderation, tangible security improvements and greater user control.
The EFF said it will remain active on other platforms such as Facebook, Instagram, YouTube and TikTok, despite its grievances and concerns around various aspects of their operations, to assist people who have no choice but to be present “in the walled gardens of the mainstream platforms”.
“We stay because the people on those platforms deserve access to information, too. We stay because some of our most-read posts are the ones criticising the very platform we’re posting on,” the nonprofit said in its blogpost, noting that its continued presence on these services “is not an endorsement”.
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It added: “X is no longer where the fight is happening. The platform Musk took over was imperfect but impactful. What exists today is something else: diminished, and increasingly ‘de minimis’.”
The EFF, founded in 1990, describes itself as “the leading nonprofit organisation defending civil liberties in the digital world”, with a stated mission “to ensure that technology supports freedom, justice and innovation for all people of the world”.
The donor-funded US nonprofit claims to use “the unique expertise of leading technologists, activists and attorneys in our efforts to defend free speech online, fight illegal surveillance, advocate for users and innovators, and support freedom-enhancing technologies”.
In the media and publishing landscape, many organisations have left X since the Musk takeover, for a variety of reasons. They include the UK’s Guardian, France’s Le Monde, and NPR and PBS in the US.
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Silicon Republic decided to stop using X in November 2024.
The plans are early-stage and Anthropic may still decide to only buy chips rather than design them. The exploration comes days after the company signed a long-term deal with Google and Broadcom for 3.5 gigawatts of TPU compute starting in 2027. A company spokesperson declined to comment.
Anthropic is exploring the possibility of designing its own AI chips, Reuters reported on Thursday, citing three sources familiar with the matter. The effort is at an early stage: the company has not committed to a specific design and has not assembled a dedicated team for the project.
It may still decide to continue purchasing chips from third parties rather than building its own. A spokesperson for the San Francisco-based company declined to comment on the report.
The exploration comes as Anthropic’s revenue has accelerated sharply. The company disclosed earlier this week that its annualised revenue run rate has surpassed $30 billion, up from approximately $9 billion at the end of 2025.
That trajectory has created a scale of compute demand that makes the economics of custom silicon increasingly worth examining. Anthropic currently runs Claude across a mix of chips: tensor processing units designed by Alphabet’s Google, in partnership with Broadcom, alongside Amazon’s custom chips and Nvidia hardware.
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The company said it matches workloads to whichever chips are best suited for them.
The filing flagged that the expanded deployment is contingent on Anthropic’s continued commercial success, an unusual hedge for a regulatory document. The deal builds on Anthropic’s November 2025 commitment to invest $50 billion in US computing infrastructure.
Broadcom is also already a chip design partner for OpenAI, and has a fifth undisclosed XPU customer, placing it at the centre of the custom AI silicon market that is emerging as an alternative to Nvidia’s general-purpose GPUs.
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The possibility of Anthropic developing proprietary silicon mirrors moves already underway elsewhere in the industry. Meta has been building its own AI training chips, and OpenAI has been working on custom silicon as well.
Industry sources cited by Reuters put the development cost of an advanced AI chip at roughly $500 million, reflecting the need to hire specialised engineers and validate the manufacturing process.
That figure is not trivial for a company that remains, for now, unprofitable, but it is more manageable against a run-rate revenue base that has more than tripled in four months.
Forgive me for this digression. I know it’s usually left to Mike Masnick to lift us up from our collective doldrums when things seem even more hopeless than they did last year. His New Year’s posts are never wrong. There are always silver linings, even if the filigree is more difficult to detect with each passing year.
This isn’t about Mike or silver linings or the as of yet unfulfilled promise of the New Year. This is a post written by a die hard defeatist and cynic who generally views each passing moment with increasing levels of defeatism.
But I’m wrong. Mike is actually right, even if my spirits often pretend they’re anchored to the ground like so many pre-oh-the-humanity German-built dirigibles.
I will tell you why I’m wrong. And it’s embarrassing. I have plenty to say about lots of stuff but I rarely convert my words into action. Recently, however, I did. And it has made all the difference.
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At the request of my oldest kid, we attended the recent “No Kings” rally in Sioux Falls. I was clad in my finest Da Share Zone anti-ICE gear:
He was wearing my protest alternate, a Black Sabbath-inspired bit of rhetoric sure to piss off white Christian nationalists:
Suitably suited, we headed to the protest with a friend of mine and his wife.
Long story short, it was life-affirming. It was exactly what anyone who feels they are losing hope needs. I feel I’m pretty good with word stuff, but I think Will Bunch absolutely nailed it in his post-No Kings column for the Philadelphia Inquirer. Quoting Marlon Brando’s mantra in The Wild One (“What are you rebelling against? Whaddya got?”), Bunch moves on to quote real people engaged in protests against something both nebulous and evil… and finding solace in being around people just like them.
“You feel less isolated when you see everybody here, and then they feel less isolated,” Nancy Harris, a 62-year-old retired mental-health crisis counselor from Prospect Park, told me over the steady car honks from supportive motorists. “And I think it just motivates people in general…just putting good vibes out into the universe.”
There’s more. Here’s a 75-year-old protester who not only knows what’s at stake, but knows why you should never give up:
“I’ve been going up against the establishment my whole life,” said [John] Coia, speaking for a generation that grew up exercising its all-American right of free speech and, now in old age, is determined to keep using it while they still can. I asked him what was the last straw with Trump that convinced him to join “No Kings.”
“There is no last straw,” he said over the car honks. “It just keeps going. There’s a new straw every day.”
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Both of these things can be true.
You can find hope in being with people who share your beliefs. You can also feel the fight is never-ending because the current administration just won’t stop being abjectly evil.
But the first thing is what matters: the government may never stop being evil, no matter who’s currently sitting behind the Resolute Desk. And people who want the government to serve the people and be less evil will always exist. The ebb and flow of these constants may shift the prevailing narrative, but it can’t undermine the actual truth — something Mike highlighted in a recent post about the horrors perpetrated by the administration in Minneapolis, Minnesota.
Here’s the quote from the Atlantic’s Adam Serwer that Mike highlighted in a long, must-read post that pointed out everything that’s right about America, even when everything seems to be going wrong:
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The secret fear of the morally depraved is that virtue is actually common, and that they’re the ones who are alone.
This is where we come together. Until recently, I believed that “coming together” was just a meeting of the minds. But that’s just preaching to the converted, which doesn’t really do much, even if my “converted” are objectively better people than the MAGA “converted.”
What really matters is that people are resisting in increasingly large numbers. We often consider the word “community” to be a cliche because that’s how the government uses it (for example, “Intelligence Community”). We view it with the same (healthy!) suspicion as we would statements delivered by company officials claiming they treat employees like “family.”
It never means anything until you’ve actually experienced (firsthand) a good one. “Family” isn’t a compliment if yours sucks. The same can be said for any “community.”
Unlike families, you can choose your community. You don’t have to align yourselves with empty mouths spewing even emptier platitudes. You just need to go out and see for yourself. Sure, I’m my own anecdata in this post. But trust me, if things feel hopeless, all you really need is the company of people who do this day in and day out, despite the table being stacked against them.
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I’m sure many (if not nearly all) of you have already had this experience. My greatest regret is that I put it off for so long. No one who truly believes in the cause will care one way or another about your day-to-day devotion. They’ll welcome you and stand beside you. Participation can be its own reward. And you’ll leave feeling more inspired to be the change we need in this world.
I just wish I had done this sooner. The world is ours. Let’s go take it.
Email apps have spent years trying to make inbox management feel faster, smarter, and less soul-crushing. But Avec seems to have looked at all that and decided the real answer was right in front of us. Just make the emails behave like a dating app.
Avec is a new mobile email app that presents your inbox to you as a stack of swipeable cards instead of the usual list view. While it may sound like a big change, the idea is pretty simple in terms of functionality. Swipe left to deal with an email later, swipe right to mark it done or archive it, and swipe down to throw less important messages into an “unimportant” pile that the app can later group together for easier cleanup.
Avec
Why this is such an interesting solution
The card-based interface is the headline here, and yes, the Tinder comparison is doing a lot of the marketing work. But Avec is aiming to reduce in-box fatigue on mobile phones, where email usually feels cramped, tedious, and too easy to ignore. The app includes a regular list-based inbox for people who aren’t ready to fully make the jump to a swipe-card style.
But this design alone could’ve made Avec into just another quirky email client. Instead, it is also leaning into voice inputs and AI.
How does AI play into this?
Avec lets users hold a button to dictate an email reply by voice. And once you stop speaking, the app turns that recording into a draft that you can review, edit, and send. This, according to founder Jonathan Unikowski, gives Avec an edge over separate keyboard-based dictation tools because the app can see the full email context, understand names, and better match tone and writing styles.
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Avec
But there’s a catch.
For now, Avec is only available in the US, and it is exclusive to the iPhone. Though it is free to use for Gmail users. Outlook support is reportedly in the works, and the company says paid tiers will come later. However, what these premium features will offer has yet to be finalized.
Humanly’s job seeker-facing product offers AI-powered coaching on interview preparation, resume writing, salary negotiation and more. (Humanly Image)
The market for recruiting software — tools that help companies find and screen candidates — is worth $14 billion. The market for actually placing people in jobs is worth $500 billion.
Humanly just raised $25 million to chase the bigger number.
The Bellevue, Wash.-based company, which makes AI-powered interviewing tools for employers, is using its new Series B funding to reposition itself as what CEO Prem Kumar calls a “service-as-a-software” company — one that doesn’t just give recruiters tools to find candidates, but delivers pre-vetted, ready-to-hire job seekers on demand. It’s less recruiting software, more staffing agency replacement.
The round included participation from SEEK Investments, Drive Capital, Zeal Capital Partners, Converge and others. Humanly has raised $52 million to date.
“I wouldn’t call it pivoting, but we’re reinventing ourselves,” Kumar said. “Instead of a tool to go out and find profiles of job seekers, we’re just giving you the candidate themselves.”
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The goal is to build a continuously refreshed database of pre-interviewed job seekers, essentially like LinkedIn’s profile network, but everyone in it has already been vetted and is ready to place.
Founded in 2018, Humanly uses automation software to help companies screen job candidates, schedule interviews, automate initial communication, run reference checks, and more. It targets customers with high volume hiring needs.
Humanly is also launching a job seeker-facing product, offering AI-powered coaching on interview preparation, resume writing, and salary negotiation — giving the company a direct relationship with candidates rather than relying solely on employer clients to funnel people into its system.
The timing may be working in Humanly’s favor. A difficult job market means more applicants chasing fewer openings, which Kumar says only amplifies the problem his company is trying to solve. AI-powered application tools have made it easier than ever for candidates to blast out applications en masse, turning virtually every open role into a high-volume hiring event. That puts more pressure on employers to filter smarter — and faster.
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Prem Kumar, CEO of Humanly, during an episode of the GeekWire series “Elevator Pitch.” in 2022. He won Startup CEO of the Year honors at the 2023 GeekWire Awards.(GeekWire File Photo)
To build out its candidate database at scale, Humanly is striking partnerships that give it access to job marketplaces where job seekers go to find work and access training. Humanly is currently conducting around 9,000 interviews per day and could gain access to an estimated 20 million job seekers over the next 12 months.
Humanly is also working with Microsoft on its neurodiversity hiring program, using AI to help neurodiverse candidates practice for technical and behavioral interviews in a structured, low-pressure environment. The partnership addresses a gap Kumar says traditional hiring processes often miss — that interview performance frequently measures communication under pressure rather than actual capability.
Through the program, candidates use Humanly’s AI avatar coach to practice explaining their thinking, walking through trade-offs, and building confidence before facing a real interviewer. Kumar has ADHD and his son was recently diagnosed, and he said the tool may also help reduce a subtler problem.
“We have a lot of data around some of the bias in human interviews,” Kumar said. “We feel an AI interviewer, interviewing someone neurodiverse, might bias against them less than humans in some cases.”
Humanly, which is No. 152 on the GeekWire 200 ranked index of the Pacific Northwest’s top startups, counts Microsoft, Domino’s, Massage Envy, Worldwide Flight Services, and MGM Resorts and Casinos among its more than 120 customers. Kumar said the company’s revenue has grown 3.9 times over the past seven months and the startup now employs about 50 people.
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Overall, Kumar sees Humanly’s shift as bigger than just its own reinvention — it’s a fundamental change in what enterprise software can now deliver.
“You no longer need to hire a big team to run a bunch of tools to get the outcome,” he said. “The tools can begin to do that themselves.”
Longtime Slashdot reader fahrbot-bot shares a report from NewScientist: According to quantum chromodynamics (QCD) — widely considered to be our best theory for describing the strong force, which binds quarks inside protons and neutrons — even a perfect vacuum isn’t truly empty. Instead, it is filled with short-lived disturbances in the underlying energy of space that flicker in and out of existence, known as virtual particles. Among them are quark-antiquark pairs. Under normal conditions, these fleeting pairs vanish almost as soon as they appear. But if enough energy is injected into a vacuum, QCD predicts they can be promoted into real, detectable particles with measurable mass. Now, the STAR collaboration — an international team of physicists working at the Relativistic Heavy Ion Collider in Brookhaven National Laboratory in New York state — has observed this process for the first time.
The team smashed together high-energy protons in a vacuum, producing a spray of particles. Some of these particles should be quark-antiquark pairs pulled directly from the vacuum itself, but quarks can never exist alone and immediately combine into composite particles. Quarks and antiquarks are born with their spins correlated — a shared quantum alignment inherited from the vacuum. The researchers found that this link persists even after the quarks and antiquarks become part of larger particles called hyperons, which decay in less than a tenth of a billionth of a second. Spotting these spin-aligned hyperons in the aftermath of the proton collisions allowed the researchers to confirm that the quarks within them came from the vacuum. The findings have been published in the journal Nature.
Google has removed popular psychological horror game Doki Doki Literature Club! from the Play Store. According to Dan Salvato, who led its development team, and publisher Serenity Forge, Google told them the visual novel was removed because it violated its Terms of Service in its depiction of sensitive themes. The game is “widely celebrated for portraying mental health in a way that meaningfully connects deeply with players around the world,” they said in their announcement. Its free version, which came out first, has been downloaded at least 30 million times, while the paid “Plus” version has had at least one million downloads. The visual novel has repeatedly made Engadget’s lists of favorite games over the years.
Doki Doki Literature Club! has the drawing style and the makings of a typical dating sim, but players find themselves confronted with serious themes, including depression and suicide, soon after starting. Its Play listing was appropriately marked as “Mature 17+,” which means that children won’t be able to download it if their devices have parental controls. In addition, the developers clearly communicate that the game tackles serious issues. “This game is not suitable for children or those who are easily disturbed” is the first line of the game. “In-game content warnings for such material can be enabled in the Settings menu at any time,” it also warns players. In settings, there’s link to a page that lists content warnings that apply to the visual novel.
We’ve asked Google for a statement on why the game was removed, and we’ll update this post when we hear back. Salvator and Serenity Forge said they’re doing everything they can to “find a path forward for getting DDLC reinstated on the Google Play Store.” They’re also looking at other methods of distribution for Android devices. At the moment, the game’s Play listing shows that it’s still not available, but it’s still out on Steam, PlayStation, Switch eshop and iOS.
Google has rolled out Device Bound Session Credentials (DBSC) protection in Chrome 146 for Windows, designed to block info-stealing malware from harvesting session cookies.
macOS users will benefit from this security feature in a future Chrome release that has yet to be announced.
The new protection has been announced in 2024, and it works by cryptographically linking a user’s session to their specific hardware, such as a computer’s security chip – the Trusted Platform Module (TPM) on Windows and the Secure Enclave on macOS.
Since the unique public/private keys for encrypting and decrypting sensitive data are generated by the security chip, they cannot be exported from the machine.
This prevents the attacker from using stolen session data because the unique private key protecting it cannot be exported from the machine.
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“The issuance of new short-lived session cookies is contingent upon Chrome proving possession of the corresponding private key to the server,” Google says in an announcement today.
Without this key, any exfiltrated session cookie expires and becomes useless to an attacker almost immediately.
Browser-server interaction in the context of the DBSC protocol source: Google
A session cookie acts as an authentication token, typically with a longer validity time, and is created server-side based on your username and password.
The server uses the session cookie for identification and sends it to the browser, which presents it when you access the online service.
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Because they allow authenticating to a server without providing credentials, threat actors use specialized malware called infostealer to collect session cookies.
Google says that multiple infostealer malware families, like LummaC2, “have become increasingly sophisticated at harvesting these credentials,” allowing hackers to gain access to users’ accounts.
“Crucially, once sophisticated malware has gained access to a machine, it can read the local files and memory where browsers store authentication cookies. As a result, there is no reliable way to prevent cookie exfiltration using software alone on any operating system” – Google
The DBSC protocol was built to be private by design, with each session being backed by a distinct key. This prevents websites from correlating user activity across multiple sessions or sites on the same device.
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Additionally, the protocol enables minimal information exchange that requires only the per-session public key necessary to certify proof of possession, and does not leak device identifiers.
In a year of testing an early version of DBSC in partnership with multiple web platforms, including Okta, Google observed a notable decline in session theft events.
Google partnered with Microsoft for developing the DBSC protocol as an open web standard and received input “from many in the industry that are responsible for web security.”
Websites can upgrade to the more secure, hardware-bound sessions by adding a dedicated registration and refresh endpoints to their backends without sacrificing compatibility with the existing frontend.
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Web developers can turn to Google’s guide for DBSC implementation details. Specifications are available on the World Wide Web Consortium (W3C) website, while an explainer can be found on GitHub.
Automated pentesting proves the path exists. BAS proves whether your controls stop it. Most teams run one without the other.
This whitepaper maps six validation surfaces, shows where coverage ends, and provides practitioners with three diagnostic questions for any tool evaluation.
Grado didn’t exactly drop this out of nowhere. When we spoke with the team at CanJam NYC 2026, there were enough hints to read between the lines, but nobody was about to say it out loud. Loose lips and all that. So we kept it quiet. Nobody wanted to end up in the East River. Now it’s official.
Grado Labs is rolling out an updated phono cartridge lineup across its Lineage, Timbre, and Prestige Series, built around targeted refinements to the stylus assembly, coil composition, and housing geometry. No reinvention, no marketing circus, just a clear effort to improve how these cartridges track, resolve detail, and behave in real-world setups.
The timing isn’t accidental. Vinyl’s resurgence has been very good to Grado’s cartridge business, but it’s also brought a flood of competition from legacy brands tightening their game to newer players looking to grab market share. Standing still isn’t an option when Ortofon, Audio-Technica, Denon, Hana, and Dynavector keep rolling out new cartridge models with every product cycle.
That’s what makes this update matter. They’re going back to the core elements that define cartridge performance and refining them across the board—better materials, tighter tolerances, and more consistency from model to model.
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And let’s be clear—John Grado and Rich Grado didn’t build this brand by coasting. This is what staying relevant looks like when you’ve been doing it since 1953.
In other words, the vinyl boom may have kept the lights on, but this is Grado making sure nobody else walks in and starts rearranging the furniture.
What’s Actually Changed: Stylus, Coils, and Housing Get Real Upgrades
The stylus assembly has been refined across the lineup, with diamond profiles and cantilever materials more carefully matched to each specific model. That matters. You’re not getting a one-size-fits-all approach anymore. Some models step up to nude Shibata diamonds, which offer better groove contact and improved tracking compared to the elliptical profiles used throughout much of the previous generation—but not every cartridge gets that upgrade, and Grado isn’t pretending otherwise.
Coils have been updated across the board with OCC copper, with purity levels scaled depending on the model. The goal is pretty straightforward: cleaner signal transmission, better channel balance, and fewer inconsistencies from unit to unit.
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On the mechanical side, the wood-bodied cartridges see revised housing geometry. This isn’t just cosmetic. The updated shapes are designed to improve stability during playback and make setup less of a headache—something anyone who has wrestled with cartridge alignment will appreciate.
Lineage Series: Grado’s Top Shelf, No Apologies
The Lineage Series sits at the top of Grado’s cartridge lineup and uses the company’s low-output moving iron, flux-bridger architecture across all three models. All three get Brazilian Ebony wood bodies, nude Shibata styli, and stereo/mono options, but the cantilever material, frequency range, resistance, and weight are not identical across the range. That’s where the pecking order starts to show.
Grado Epoch4 — $9,995
The Epoch4 is the flagship. It uses a Brazilian Ebony wood body, sapphire cantilever with Shibata diamond, 1.0mV output at 5 CMV (45 degrees), 5 Hz to 75 kHz controlled frequency response, average 35 dB channel separation from 10-30 kHz, 10-47k ohm input load, 8mH inductance, 95 ohms resistance, 10.5 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 μm/mN compliance. Grado also says the internal signal path uses ultra-high purity OCC copper with gold plating, and that the cartridge undergoes cryogenic treatment during component prep and final assembly.
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Grado Aeon4 — $4,995
The Aeon4 keeps the Brazilian Ebony body and sapphire/Shibata combo, with the same 1.0mV output, 10-47k ohm input load, 8mH inductance, 10.5 gram weight, 1.6-1.9 gram tracking force, and 20 μm/mN compliance. Where it differs from the Epoch4 is the controlled frequency response, which is listed at 5 Hz to 70 kHz, and resistance, which drops to 74 ohms. Grado specifies ultra-high purity 7N OCC copper here. In other words, still serious, just not wearing the full tux.
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Grado Statement4 — $3,500
The Statement4 is the entry point into the Lineage family, but it is not a stripped-down tourist model. It uses a Brazilian Ebony wood body and swaps to a machined boron cantilever with Shibata diamond. Specs include 1.0mV output at 5 CMV (45 degrees), 5 Hz to 65 kHz controlled frequency response, average 35 dB channel separation from 10-30 kHz, 10-47k ohm input load, 8mH inductance, 74 ohms resistance, 10 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 μm/mN compliance. Like the Aeon4, it uses ultra-high purity 7N OCC copper and cryogenic treatment.
Timbre Series: Where Grado Dials It In for the Real World
The Timbre Series is where Grado Labs hits the balance point—high-end analog performance without drifting into Lineage-level pricing. This is the middle of the lineup, but it’s not a compromise. It’s a deliberate tuning exercise.
Across the range, Grado sticks with elliptical diamond styli and its moving iron, flux-bridger design. The emphasis here isn’t on any single upgrade—it’s on how everything works together. Stylus profile, cantilever material, coil composition, and housing are treated as a system, not a checklist. The result is a presentation that leans into tonal balance, coherence, and musical flow rather than hyper-detail for its own sake.
Material choices define the hierarchy. The Reference3 and Master3 use American Osage wood bodies with boron cantilevers for greater control and resolution, while the Sonata3 and Platinum3 move to Mediterranean Olive wood paired with aluminum cantilevers. The Opus3, built from American Maple, rounds things out with a simpler aluminum cantilever configuration. Same core design philosophy throughout, just scaled in execution.
Grado Reference4 — $1,500
The Reference4 sits at the top of the Timbre Series. It uses an American Osage wood body, machined boron cantilever with Shibata diamond, 4.0mV high output or 1.0mV low output at 5 CMV (45 degrees), 10 Hz to 60 kHz controlled frequency response, average 30 dB channel separation from 10-30 kHz, 10k-47k ohm input load, 55mH inductance in high output and 6mH in low output, 660 ohms resistance in high output and 70 ohms in low output, 9.6 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 μm/mN compliance. Grado also specifies ultra high purity 6N OCC copper in the internal signal path, along with cryogenic treatment and internal damping.
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Grado Master4 — $1,000
The Master4 uses an American Osage wood body, machined boron cantilever with elliptical diamond, 4.0mV high output or 1.0mV low output at 5 CMV (45 degrees), 10 Hz to 60 kHz controlled frequency response, average 30 dB channel separation from 10-30 kHz, 10k-47k ohm input load, 55mH inductance in high output and 6mH in low output, 660 ohms resistance in high output and 70 ohms in low output, 9.6 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 μm/mN compliance. It is offered in high output, low output, and mono versions.
Grado Sonata4 — $600
The Sonata4 uses a Mediterranean Olive wood body, special aluminum cantilever with elliptical diamond, 4.0mV high output or 1.0mV low output at 5 CMV (45 degrees), 10 Hz to 60 kHz controlled frequency response, average 30 dB channel separation from 10-30 kHz, 10k-47k ohm input load, 55mH inductance in high output and 6mH in low output, 660 ohms resistance in high output and 70 ohms in low output, 9.4 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 μm/mN compliance. It is also offered in high output, low output, and mono versions.
Grado Platinum4 — $400
The Platinum4 uses a Mediterranean Olive wood body, aluminum cantilever with elliptical diamond, 4.0mV high output or 1.0mV low output at 5 CMV (45 degrees), 10 Hz to 60 kHz controlled frequency response, average 30 dB channel separation from 10-30 kHz, 10k-47k ohm input load, 55mH inductance in high output and 6mH in low output, 660 ohms resistance in high output and 70 ohms in low output, 9.4 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 μm/mN compliance. It is available in high output, low output, and mono versions.
Grado Opus4 — $300
The Opus4 is the entry point into the Timbre Series. It uses an American Maple wood body, aluminum cantilever with elliptical diamond, 4.0mV high output or 1.0mV low output at 5 CMV (45 degrees), 10 Hz to 60 kHz controlled frequency response, average 30 dB channel separation from 10-30 kHz, 10k-47k ohm input load, 55mH inductance in high output and 6mH in low output, 660 ohms resistance in high output and 70 ohms in low output, 8.3 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 μm/mN compliance. Grado says the internal signal path uses ultra high purity 5N OCC copper, with cryogenic treatment and internal damping as part of the build process.
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Prestige Series: Where Grado Keeps It Simple and Affordable
The Prestige Series is the foundation of what Grado Labs has been doing for decades and it hasn’t survived this long by accident. This is the entry point into the lineup, but it’s built on a design that’s been refined over more than fifty years, not reinvented every product cycle. Those paying attention will notice that the lineup has been trimmed down.
Across the range, Grado sticks with elliptical diamond styli, aluminum cantilevers, and its moving iron, flux-bridger design. The goal here isn’t to chase ultimate resolution—it’s consistency. Strong tracking, a balanced tonal presentation, and performance that doesn’t drift over time. These are cartridges designed to work, not impress on spec sheets.
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One of the biggest advantages in the Prestige Series is the user-replaceable stylus system. When the stylus wears out, you don’t toss the cartridge, you swap the stylus and keep going. It’s practical, cost-effective, and a big part of why these have remained popular with both newcomers and long-time vinyl listeners.
No exotic wood bodies here, no sapphire cantilevers, just a straightforward design that prioritizes reliability and ease of use without abandoning the Grado house sound.
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Grado Prestige Gold4 — $260
The Prestige Gold4 sits at the top of the current Prestige Series. It uses a four piece OTL cantilever with a Grado specific elliptical diamond stylus mounted on a brass bushing, 4 mV output at 5 CMV (45 degrees), 10 Hz to 55 kHz frequency response, average 25 dB channel separation from 10-30 kHz, 10k-47k ohm input load, 50 mH inductance, 660 ohms DC resistance, 6 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 um/mN compliance. Grado also says the Gold4 uses a machined turned generator for lower distortion and greater transparency, along with ultra high purity copper wire and its twin magnet / Flux-Bridger moving iron design.
Grado Prestige Red4 — $190
The Prestige Red4 uses a bonded elliptical diamond mounted to an aluminum cantilever, 4 mV output at 5 CMV (45 degrees), 10 Hz to 55 kHz frequency response, average 25 dB channel separation from 10-30 kHz, 10k-47k ohm input load, 50 mH inductance, 660 ohms DC resistance, 6 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 um/mN compliance. Grado describes it as a high output moving iron cartridge and notes that the stylus assembly is user-replaceable, with Prestige Series styli interchangeable across models.
Grado Prestige Green4 — $140
The Prestige Green4 uses a bonded elliptical diamond mounted to an aluminum cantilever, 4 mV output at 5 CMV (45 degrees), 10 Hz to 55 kHz frequency response, average 25 dB channel separation from 10-30 kHz, 10k-47k ohm input load, 50 mH inductance, 660 ohms DC resistance, 6 gram cartridge weight, 1.6-1.9 gram tracking force, and 20 um/mN compliance. Grado also describes it as a high output moving iron cartridge with a user-replaceable stylus assembly, available in both standard mount and P-mount versions.
Trade-In Program: Grado’s Answer to Cartridge Burnout
Grado takes a different approach to long-term ownership, and it’s one that actually makes sense if you’ve been around analog long enough to know how this usually goes.
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For its wood-bodied models, Grado Labs offers a cartridge trade-in program that lets you send back your existing cartridge; no matter how worn, and apply it toward a new one at a reduced cost. No drama, no “must be in mint condition” nonsense.
The idea is simple: keep people in the ecosystem without forcing them to start from scratch every time their stylus wears down or their system evolves. Instead of treating cartridges as disposable, Grado treats them like part of a longer-term upgrade path.
That flexibility cuts both ways. You can move up the range if you’re chasing more performance, or step sideways or even downward if your system changes or priorities shift. Either way, you’re getting a current production model with the latest refinements baked in. You won’t get that from Denon, Hana, or Clearaudio.
The Bottom Line
Grado didn’t reinvent anything—they refined the parts that actually matter. Across Lineage, Timbre, and Prestige, the updates focus on improved stylus assemblies, higher-purity OCC copper coils, and revised housing geometry, all aimed at better tracking, consistency, and easier setup.
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On paper, the lineup is clearly tiered: Lineage pushes materials and resolution at the top, Timbre balances performance and design choices in the middle, and Prestige continues as the accessible, user-friendly foundation with its replaceable stylus system. Each range sticks to the same moving iron DNA, just executed at different levels.
Who should pay attention? Anyone with a vinyl setup who hasn’t looked at Grado in a while—and especially those watching how established brands respond to a more competitive cartridge market.
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