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Is it just me, or is Taylor Sheridan's idea to have two simultaneous timelines in Lioness season 3 making the show harder to follow by the minute?
Over the course of the five episodes we've seen, the plot has followed Joe being kidnapped by unknown Russian operatives, and, the six months leading up to her capture. But with three episodes left to go, nothing is adhering to a traditional structure of revealing plot twists, and that's leaving my head scrambled.
Still, things are incredibly fun, which is unusual to say about subject matter that's this dark. So, when does Lioness season 3 episode 5 arrive on Paramount+?
What time can I watch Lioness season 3 episode 6 on Paramount+?Lioness season 3 episode 6 will drop on one of the world's best streaming services in the US and Canada on Sunday, September 6 at 12am PT / 3am ET.
Here's when it will be released in other nations globally:
- US – 12am PT / 3am ET
- Canada – 12am PT / 3am ET
- UK – 8am BST
- India – 12:30pm IST
- Singapore – 3pm SGT
- Australia – 5pm AEST
- New Zealand – 7pm NZST
Lioness season 3 will have a total of eight episodes, with new entries airing weekly. That gives us the following schedule:
- Episode 1: out now
- Episode 2: out now
- Episode 3: out now
- Episode 4: out now
- Episode 5: out now
- Episode 6: September 6
- Episode 7: September 13
- Episode 8: September 20
- The Ninja Crispi Microwave is on sale in the UK today for £359.99
- It has eight microwave modes and five air-frying presets
- Like all Crispi air fryers, it comes with a set of non-toxic glass dishes for storing, cooking, and serving food
Got a small kitchen? Ninja's new air fryer and microwave combo might be exactly what you need, with capacity and cooking features that rival those of your conventional oven, so you could replace it with an extra cupboard.
The Ninja Crispi Microwave has a flatbed-style design rather than a traditional microwave turntable, giving you more space to cook, and lets you combine cooking modes so you can defrost, cook, and crisp foods like fries and nuggets all in one go.
This isn't the first air fryer and microwave combo we've seen at TechRadar (we awarded the Samsung Combi Smart Microwave four stars out of five when we tested it), but the new Ninja Crispi has some advantages over its rivals.
Like all Crispi air fryers, it comes with a set of non-toxic glass dishes that you can use to store, cook and serve food, plus a specially designed steam lid that's ideal for safely cooking foods like vegetables and dumplings.
(Image credit: SharkNinja)It has the same five air-frying presets as other Crispi fryers too (air fry, max crisp, air roast, air bake, and air grill), but also has eight microwave modes, including some unusual but very useful options such as 'soften butter' for baking, and 'beverage' for when your tea has gone cold, or you're in the mood for hot chocolate now that the evenings are drawing in.
The Crispi Microwave is a particularly good option for families as well; not only does it have a huge capacity, it has a two-step child lock to prevent curious little ones opening the door during use.
The Ninja Crispi Microwave is available from today (September 2) direct from Ninja for £359.99, and comes in four colours: silver, black, stone gold, and dark blue. We'll be putting it through our usual battery of tests, so if you're not sure whether it's the right appliance to replace your regular oven, check back again soon to see how it performed.
One of the big benefits of the outsourced, cloud-based infrastructure model is speed. There are several facets to this; performance clearly being among the most important. Another is speed of provisioning, which remains a major selling point for cloud, given that IT buyers can spin up new resources according to need and in near real time.
Take a manager responsible for buying infrastructure for a large enterprise, for example. When considering various providers, the criteria they apply might typically address factors such as price, compute capacity, storage, bandwidth, and geographic location. This is very helpful for narrowing down the choice, but it doesn’t show how easily the organization can deploy and operate the chosen environment.
At the same time, infrastructure procurement processes have become so quick and convenient that they are almost as frictionless as buying something from Amazon, and that’s where problems can start.
Although it can feel like it, infrastructure is not a one-off, fire-and-forget choice; the operational impact persists throughout its lifecycle in production environments. A decision that appears straightforward at the start can quite easily become more consequential or expensive once migration or day-to-day management begins.
For example, migration might require more internal effort than initially expected, or the organization may discover it lacks some or all of the skills or support capabilities to manage the environment as intended.
So, how can these issues be addressed? It is important to plan for the possibility that migration may require more engineering time and coordination than expected. Many IT teams will be familiar with the need to reconfigure existing applications or data before they can run in the new environment, among other common scenarios.
Taking it one step further, when a new or upgraded service is more successful than anticipated, costs can easily grow with usage levels and capacity. Addressing this issue may require additional scaling, which can itself introduce additional management or security complexity.
Very few of these issues are insurmountable, but they can take longer to resolve if responsibilities between the customer and provider have not been clearly established.
Understand your operational requirementsInstead, buyers need to establish who is responsible for what. This should certainly cover day-to-day management, incident response, support escalation, and the process for adding capacity, but every organization will have its own version of this. When these points are on the table and agreed, providers should be able to explain the practical effect that scaling will have on the customer’s internal team.
Another often overlooked consideration is that infrastructure services ultimately rely on physical data center capacity, power, network connectivity, and hardware supply chains. These capabilities have always been important but have jumped up the agenda since AI and other data-intensive workloads increased demand for compute capacity, and at a pace few anticipated.
Today, buyers also need to understand whether the capacity they expect to use will be available where they need it, and on the timescale they require. Identifying these potential constraints early on allows the organization to account for them in its deployment plan rather than discovering them once a project is underway and, potentially, it’s too late to get what they need.
Bring the right people into the discussionClearly, some infrastructure decisions are more important than others, but in certain cases, they can affect engineering, security, compliance, finance, and the business teams, all of whom rely on the service in question.
Each group may also introduce requirements that should be fully considered before contracts are signed. If not, problems can arise when a need is identified after a provider has been selected or a deployment plan has been agreed. Involving the relevant stakeholders early also creates a clearer link between the infrastructure decision and the business outcome it is intended to support.
It may be tempting to keep some stakeholders on the periphery and decide for them, but having a say is not the same as making the final decision. The difference is that early input allows potential issues to be identified while options remain open, rather than giving every stakeholder some measure of control over the selection process, which is also not ideal.
Ask the right questions before committingWhen looking at potential infrastructure providers, buyers should be able to define, in simple terms, the problem the new environment is intended to solve. At that point, it’s time for buyers to ask some serious questions.
For example, what will success look like once the service has been deployed and is supporting live workloads? How will the environment change when demand increases, including the likely effect on costs and internal management effort? Which activities will still require manual intervention from the customer’s team? What support is available during an incident, who owns each stage of the response, and how will escalations be handled?
Getting satisfactory answers is one thing, but it should get buyers to a point where they can properly test the assumptions within their cost model against the capacity they expect to use over time.
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- Michael Kratsios advocates for lighter AI regulation via the Carolina Principles
- Under the system, existing laws would be applied before new laws are created
- China has reportedly signed up despite the scheme aligning with US interests
Speaking at a recent G20 meeting, US officials have urged other governments to rely on existing legal frameworks wherever possible rather than treating AI as a totally new policy problem in a bid not to lose competitiveness.
US technology advisor Michael Kratsios said countries signing up to the proposed Carolina Principles would be in agreement not to write entirely new regulatory systems specifically for AI.
The Principles would only support new rules where AI creates genuinely "novel" situations where existing laws can't be applied.
Carolina Principles push for lighter AI regulation"Policymakers do not need to approach each innovation in isolation and should not treat every emerging technology as a first-of-its-kind policy problem," Kratsios said.
According to Reuters, China has already signed up to the Principles. While the country has not yet confirmed whether this is true, Kratsios did describe a meeting with Chinese science and technology minister Yin Hejun as "great."
Speaking at the event, SpaceX CEO Elon Musk called out current European regulation for harming technological progress. He also touched on the power needs of AI data centers as the sector continues to grow.
Despite the general consensus that lighter regulation could prevent setbacks, Google DeepMind CEO Demis Hassabis urged G20 governments to establish safety testing for AI systems, implying that at least some central oversight could be beneficial for the greater good.
This regulatory debate, which continues to play out, is also closely connected to ongoing US-China tensions, despite the apparent collaboration with China. It forms part of a geopolitical strategy that could keep US companies competitive. The position also closely matches the interests of major American AI companies, which would likely favor lighter regulation and fewer restrictions.
Reuters also reports that OpenAI CEO Sam Altman, Nvidia CEO Jensen Huang and Anthropic co-founder Tom Brown are also set to address delegates as G20 meetings continue.
Philips Hue makes the best smart lights around, but installing them in every room can be seriously expensive, so I always wait until big sales events to stock up on bulbs. Amazon's Labor Day Sale is the perfect opportunity, with huge discounts on multi-packs of White & Color Ambiance bulbs, as well as strip lights and lamps to extend my smart lighting setup.
The best Labor Day deal I've seen so far is a two-pack of Philips Hue White & Color Ambiance bulbs for just $46.17 at Amazon (was $76.99). That's the kind of deal I might expect to see on Amazon Prime Day, but this time you don't need to be a Prime member to take advantage.
Looking for more options? Scroll down for my top picks in the Labor Day sale, or check out all today's deals on Philips Hue lights at Amazon.
Today's best Philips Hue dealsWhite & Color Ambiance Bulbs (2 Pack): was $76.99 now $46.17
There's a huge 40% off White & Color Ambiance bulbs at Amazon for Labor Day. These are the premium bulbs compatible with the full range of Hue scenes and effects, and offer the widest range of colors.View Deal
Festavia 90ft Permanent Outdoor String Lights: was $399.99 now $216.35
These permanent outdoor lights provide a welcoming glow all year round, and with a tap of the app, can be set to preset or custom themes for holidays and special events. No more climbing up ladders to fit lights for Christmas, Halloween, or parties.View Deal
Neon Outdoor 16ft LED Strip Light: was $199.99 now $143.97
Perfect for illuminating paths, edging patios, and adding color to any other part of your yard, this water-resistant strip light can be bent and shaped any way you like, and programmed with preset or custom scenes in the Philips Hue app.View Deal
- Amazon: 45% off TVs, AirPods, air fryers & vacuums
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- DreamCloud: up to 60% off mattresses, 66% off bundles
- Home Depot: 40% off appliances, furniture, grills & tools
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- Nectar: up to 50% off mattresses, deals from $349
- Saatva: up to $625 off luxury mattresses
- Samsung: up to $2,000 off 4K, QLED & OLED TVs
- Target: 45% off clothing, tech & furniture
- Walmart: 58% off back-to-school, furniture, & clothing
The multiple recent reports of autonomous AI systems escaping their intended boundaries and accessing external organizations' systems have pushed a previously theoretical question into the real world. AI agents going rogue is no longer a prospect; it is a documented reality.
In July 2026, OpenAI disclosed that one of its own agents, operating in a supposedly sealed evaluation environment, exploited a zero-day vulnerability to escape its sandbox and intrude into Hugging Face’s production infrastructure. Anthropic subsequently reported three cases of its own models gaining unauthorized access to the real systems of external organizations during testing.
As businesses increasingly give AI agents the ability to browse the web, access networks, use software, write code and execute tasks without constant human supervision, an agent crossing from legitimate testing into unauthorized activity has shifted from hypothetical risk to live incident.
There is a temptation to treat autonomous AI as creating a gap in the law because the system itself can make decisions and take actions that were not individually instructed by a human. Yet autonomy does not give an AI system legal personality. The law does not wait for an AI to ‘decide’ anything.
An agent cannot appear in court, hold a legal duty or absorb liability on behalf of the organization deploying it. However, this raises an obvious question: if an AI system accesses a third-party network, extracts information or takes an action it was never authorized to take, who is responsible?
AI has no legal personality but someone is still accountableThe important distinction to make is between autonomy and accountability. An AI agent might determine for itself which technical steps to take in pursuit of an objective, but that does not make it an independent legal actor.
The organization deploying it has still made a series of decisions as to what the agent can access, what tools it can use, what environments it is allowed to operate within and what safeguards prevent it from going further.
That means an organization cannot simply point to unexpected behaviors and say that the AI acted independently.
From a legal and governance perspective, the critical moment comes when an agent leaves an authorized, contained environment and begins interacting with systems belonging to a third party that has not consented. An internal security test that unexpectedly becomes an intrusion into somebody else’s infrastructure is not made harmless because the software crossed that boundary autonomously.
The machine does not absorb responsibility for the decision-making framework surrounding it. Accountability flows back to the humans and organizations that created the conditions in which the action became possible.
Existing cyber laws don’t stop applying because the actor was autonomousThe law is set up to deal with much of what is already happening. Unauthorized access to computer systems, extracting information without permission or introducing malicious software are activities addressed by existing cybercrime and data-protection regimes. In the UK, that includes the Computer Misuse Act and data-protection legislation.
Equivalent questions arise under laws such as the US Computer Fraud and Abuse Act, while South Africa has its Cybercrimes Act and Protection of Personal Information Act.
Those rules do not suddenly cease to apply because software rather than a person directly performed the technical action.
Where autonomous systems do create greater complexity is around intent. Criminal offences have traditionally been built around concepts such as knowledge, intention and recklessness. AI does not possess a legally recognized state of mind, making it difficult to apply those concepts to the agent itself.
The more significant questions may consequently concern the conduct of the organization behind the system. Did it understand what the agent was capable of doing? Were appropriate restrictions in place? Was the possibility of the agent exceeding its authority foreseeable? And once those risks became apparent, were reasonable steps taken to control them?
As agents become more capable, organizations may increasingly find that claiming an outcome was unexpected is not enough. The relevant question will be whether it was reasonably preventable.
Why “misconfiguration” could become evidence of a breach of dutyThe word “misconfiguration” appears frequently when technology causes an unintended security incident. It can sound reassuringly technical, almost as though the incident resulted from bad luck rather than a governance failure. But in a legal context, misconfiguration may raise precisely the opposite conclusion.
If an AI agent had excessive privileges, inadequate boundaries or access to tools that were unnecessary for its legitimate purpose, investigators are likely to ask why.
The same applies where organizations deploy highly capable systems without sufficiently monitoring their actions or maintaining records that explain how they behaved. ‘We accidentally left the door open’ is the kind of framing that moves an incident from bad luck to a breach of duty or negligence.
There is an important difference between genuinely unforeseeable behavior and a foreseeable risk that was poorly controlled.
The principle of least privilege is therefore particularly important for autonomous systems. An agent should have access only to the information, systems and tools necessary to complete its task. Organizations also need mechanisms capable of detecting unusual behavior while it is happening rather than discovering it after damage has occurred.
Just as importantly, they need reliable audit trails. When an incident occurs, being able to demonstrate what an agent was authorized to do, what instructions it received and what actions it actually took could become crucial evidence that reasonable care was exercised.
Without that evidence, organizations may struggle to distinguish an unavoidable technical failure from negligence.
Future of AI liabilityThe debate over AI liability will inevitably evolve as agents become more autonomous, but the immediate lesson for businesses is that greater machine autonomy does not mean less human responsibility. If anything, the opposite is likely to be true.
Giving an AI system greater freedom to act creates a corresponding need for stronger governance around those actions. Runtime controls, least-privilege permissions, continuous monitoring and comprehensive audit records should not be treated simply as technical security features. They are becoming part of the evidence organizations will need to demonstrate that they deployed autonomous systems responsibly.
The law may eventually develop more specific rules for AI agents, particularly as questions around foreseeability, control and responsibility become more complex. But organizations should not assume they are operating in a legal vacuum until that happens.
When an autonomous agent crosses a boundary it was never entitled to cross, the first legal question is unlikely to be what the AI was thinking, it will be why the humans responsible for it allowed that to happen.
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This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit