Spoilers for Secret Levels Pac-Man episode follow.Pac-Man: Circle is the one episode of Secret Level thats truly unforgettable.Recommended VideosWhile most of Amazons new gaming anthology TV series plays it very safe, Pac-Man: Circle takes a radical new direction. The episode sees an alien-looking man called the Swordsman freed by an ominous spherical orb called Puck. While Puck is obviously supposed to be Pac-Man, Emily Swallows excellent portrayal of this character sounds more like Hal 9000 from 2001: A Space Odyssey than any voiced version of the character weve seen before. Puck constantly reminds the Swordsman that theyre trapped in a maze they need to break free of and that its eat or be eaten if you want to survive.You are the chosen. Enter p4cm4n @ entersecretlevel.com #SecretLevelPac-Man: Circle is a bloody, violent, and subversive interpretation of a game typically touted for its universal appeal. As I watched it, it was hard to believe Bandai Namco would encourage such an episode to be associated with Pac-Man, but executive producer Dave Wilson tells Digital Trends that Bandai Namco Entertainment outright encouraged it.They really just threw down the gauntlet, Wilson says. Through the translator, the mission statement from Bandai was: We would like audiences to wonder what the f**k they did with Pac-Man.According to Wilson, Secret Levels writers room distilled the elements of Pac-Man down to single lines that appear in the episode, such as eat or be eaten and you can eat them, but never their eyes. Those serve as the basis for the tragic, mature story this episode of Secret Level tells through the basic framework of Pac-Man. On the visual front, the episodes look was inspired by artists like Moebius and Pascal Blanchet, leaning into vivid colors while not being afraid to have some grit.Wilson and executive producer Tim Miller admitted to Digital Trends that many other elements of Pac-Man: Circle were established early on and stayed relatively similar throughout development. Swallow, whose voice you may recognize as The Armorer from The Mandalorian, and Aleks Le, who portrayed Luke in Street Fighter 6, came in as the voices of Puck and the Swordsman early on in the story reel process and werent ever replaced by other actors. Wilson said hed love to release the story reel at some point so people can see how close it is.AmazonPac-Man: Circle is much longer than other episodes of its ilk in Secret Level because the developers stuck so closely to the original vision. Wilson explained that the episode was originally supposed to only be 5 minutes long, but Illusorium Studios story reel for the episode came in at 9 minutes. Wilson and Miller thought it would be sacrilege to cut it half, so they gave Illusorium a choice of whether to keep it at the longer length or cut it in half. Illusorium chose to put in the extra work to realize the full vision for Pac-Man: Circle.In its boldness, Pac-Man: Circle is Secret Level at its best. The series low points are the slower, more dialogue-filled episodes that can feel like a marketing ploy for games like New World: Aeternumor PlayStation as a brand. Episodes that lean into action (like the Gladiator-riffing Unreal Tournament episode) or take large creative risks like Pac-Man: Circle are the most enjoyable to watch.If I only get one shot, I want to be able to do whatever the f**k I want.This anthologys oddball collection of adaptations has an eclectic feeling, but to its creators, that variety is part of Secret Levels beauty. Miller is appreciative that so many companies, from Bandai Namco to the console publishers, were willing to work together and be included alongside each other in Secret Level.You could think that they might want to go off into their separate marketing corner and jealously guard their IP, but they dont, Miller tells Digital Trends. They all came together in a really joyous, eager way. I think they like the fact that its this sort of jam session between the whole game industry, from indies to classics to games that havent come out yet to blockbuster AAA stuff thats on the market now.Prime VideoIt also may have helped that Miller didnt have a preexisting notion of wanting to connect all of the episodes together narratively or thematically. Especially with an anthology based on games, I didnt want to limit it to just one genre or one type of game If I only get one shot, I want to be able to do whatever the f**k I want or that I think might make a cool story.While that approach resulted in some duds, it also gave us a few unforgettable episodes like Pac-Man: Circle. Regardless of the uneven quality of the overall show, theres solace to be taken from the fact that some episodes were able to take brave leaps of faith and reinterpret the classic franchises they were based on. This makes an episode like Pac-Man: Circle that does just that well worth watching.Pac-Man: Circle and several other Secret Level episodes are now available on Prime Video. Another batch of Secret Level animated shorts will drop on December 17.Editors RecommendationsConcord returns from the dead in Amazons Secret Level trailer

CruiseAutonomous-driving operations at Cruise look certain to end after its main backer, General Motors (GM), said it will stop funding the initiative.GM, which has owned about 90% of Cruise since 2016, announced the decision in a statement shared on Tuesday. It follows a challenging period for Cruise after one of its autonomous cars ran over a woman after she was knocked into its path by a human-driven car in San Francisco in October 2023. The incident led to California regulators suspending Cruises license to test its driverless cars on the states streets, a decision that prompted Cruise to pause operations in other locations where it operated. It restarted low-level testing in Arizona in May 2024.Recommended VideosGM, which has invested billions of dollars in Cruise, said on Tuesday that it will no longer fund Cruises robotaxi development work given the considerable time and resources that would be needed to scale the business, along with an increasingly competitive robotaxi market, adding that it plans to combine Cruise and GM technical teams into a single unit that will focus on advancing autonomous and assisted driving. GM is committed to delivering the best driving experiences to our customers in a disciplined and capital efficient manner, Mary Barra, CEO of GM, said in the statement. Cruise has been an early innovator in autonomy, and the deeper integration of our teams, paired with GMs strong brands, scale, and manufacturing strength, will help advance our vision for the future of transportation.RelatedDave Richardson, senior vice president of software and services engineering at GM, said the automaker is fully committed to autonomous driving and excited to bring GM customers its benefits things like enhanced safety, improved traffic flow, increased accessibility, and reduced driver stress.Cruise has yet to comment publicly on GMs decision to end funding and how it will impact its autonomous testing in the immediate future. The company has driverless cars on roads in Texas and Arizona, but GMs announcement could see Cruise pause operations with immediate effect. Digital Trends has reached out to Cruise for comment and we will update this article when we hear back.GMs decision highlights the difficulties in making the fledgling robotaxi industry that currently comprises mostly pilot services. In a similar move, another major automaker, Ford, pulled funding for autonomous-car specialist Argo in 2022. Alphabet-backed Waymo, which tests its robotaxis in multiple cities and recently announced it will be launching in Miami, is the current leader in the field.Editors Recommendations

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Moxie Startup will brick $800 emotional support robot for kids without refunds Embodied says it will try to refund recent purchases but makes no promises. Scharon Harding Dec 10, 2024 4:55 pm | 25 Parents are determining how to tell their kids that their robot friend will stop playing with them. Credit: Embodied Parents are determining how to tell their kids that their robot friend will stop playing with them. Credit: Embodied Story textSizeSmallStandardLargeWidth *StandardWideLinksStandardOrange* Subscribers only Learn moreStartup Embodied is closing down, and its product, an $800 robot for kids ages 5 to 10, will soon be bricked.Embodied blamed its closure on a failed critical funding round." On its website, it explained:We had secured a lead investor who was prepared to close the round. However, at the last minute, they withdrew, leaving us with no viable options to continue operations. Despite our best efforts to secure alternative funding, we were unable to find a replacement in time to sustain operations.The company didnt provide further details about the pulled funding. Embodieds previous backers have included Intel Capital, Toyota AI Ventures, Amazon Alexa Fund, Sony Innovation Fund, and Vulcan Capital, but we don't know who the lead investor mentioned above is.When it first announced Moxie in April 2020, Embodied described the robot as a safe and engaging animate companion for children designed to help promote social, emotional, and cognitive development. It advertised play built around best practices in child development and early childhood education; changing weekly themes, like empathy, friendship, and respect; and activities like meditation, reading, and drawing with the bot.But soon, none of those features will be available, making the pricey childrens toy virtually useless. According to Embodied, Moxie cant perform core functionality with cloud connectivity. Worse, owners apparently have an uncertain and limited amount of time until the devices are bricked. Per Embodied:We dont know the exact date when services will cease. It is likely to happen within days. However, we are exploring options to keep Moxie operational for as long as possible, although we cannot provide any guarantees.Since Embodied marketed Moxie as a companion and development toy for children, theres concern about kids potentially suffering an emotional toll after the robot abruptly becomes inoperable. Embodied has responded by promising to provide a guide for telling children about Moxie's demise. Online, however, customers are already sharing videos of their sad kids learning that their robot friend will stop playing with them, as Axios pointed out.In addition to the robot being bricked, Embodied noted that warranties, repair services, the corresponding parent app and guides, and support staff will no longer be accessible.Unable to offer refundsEmbodied said it is unable to offer most Moxie owners refunds due to its financial situation and impending dissolution. The potential exception is for people who bought a Moxie within 30 days. For those customers, Embodied said that if the company or its assets are sold, we will do our best to prioritize refunds for purchases," but it emphasized that this is not a guarantee.Embodied also acknowledged complications for those who acquired the expensive robot through a third-party lender. Embodied advised such customers to contact their lender, but its possible that some will end up paying interest on a toy that no longer works.Embodied said its looking for another company to buy Moxie. Should that happen, the new company will receive Embodied customer data and determine how it may use it, according to Embodieds Terms of Service. Otherwise, Embodied said it securely erases user data in accordance with our privacy policy and applicable law, which includes deleting personally identifiable information from Embodied systems.Another smart gadget bites the dustCurrently, theres some hope that Moxies can be resurrected. Things look grim for Moxie owners, but weve seen failed smart device companies, like Insteon, be resurrected before. It's also possible that someone will release of an open-source version of the product, like the one made for Spotify Car Thing, which Spotify officially bricked today.But the short-lived, expensive nature of Moxie is exactly why some groups, like right-to-repair activists, are pushing the FTC to more strongly regulate smart devices, particularly when it comes to disclosure and commitments around software support. With smart gadget makers trying to determine how to navigate challenging economic landscapes, the owners of various types of smart devicesfrom AeroGarden indoor gardening systems to Snoo bassinetshave had to deal with the consequences, including broken devices and paywalled features. Last month, the FTC noted that smart device manufacturers that dont commit to software support may be breaking the law.For Moxie owners, disappointment doesnt just come from wasted money and e-waste creation but also from the pain of giving a child a tech companion to grow with and then have it suddenly taken away.Scharon HardingSenior Product ReviewerScharon HardingSenior Product Reviewer Scharon is Ars Technicas Senior Product Reviewer writing news, reviews, and analysis on consumer technology, including laptops, mechanical keyboards, and monitors. Shes based in Brooklyn. 25 Comments

Hi, we're the replacements AI company trolls San Francisco with billboards saying stop hiring humans Company boasts "AI workers" that never complain about work-life balance. Benj Edwards Dec 10, 2024 3:43 pm | 123 An advertisement for the AI company Artisan is posted on 2nd Street on December 05, 2024 in San Francisco. Credit: Justin Sullivan via Getty Images An advertisement for the AI company Artisan is posted on 2nd Street on December 05, 2024 in San Francisco. Credit: Justin Sullivan via Getty Images Story textSizeSmallStandardLargeWidth *StandardWideLinksStandardOrange* Subscribers only Learn moreSince the dawn of the generative AI era a few years ago, the march of technologytoward what tech companies hope will replace human intellectual laborhas continuously sparked angst about the future role humans will play in the job market. Will we all be replaced by machines?A Y-Combinator-backed company called Artisan, which sells customer service and sales workflow software, recently launched a provocative billboard campaign in San Francisco playing on that angst, reports Gizmodo. It features the slogan "Stop Hiring Humans." The company markets its software products as "AI Employees" or "Artisans."The company's billboards feature messages that might inspire nightmares among workers, like "Artisans won't complain about work-life balance" and "The era of AI employees is here." And they're on display to the same human workforce the ads suggest replacing.Preying on AI angstThe reaction to the ads online has been largely negative. Last week, a Bluesky user named SpacePrez posted one of the billboards on the social media site simply with the comment, "AAAAAAAAAAAAAAAAAAAAAAAGH." It currently has over 2,000 likes.On Reddit, a thread featuring the ads filled with pessimistic commentary on life in San Francisco, including comments like, "Its close to full Cyberpunk dystopia over here when we have self driving Waymos driving through neighborhoods with tent cities where apartments cost $4k a month."Artisan CEO Jaspar Carmichael-Jack defended the campaign's messaging in an interview with SFGate. "They are somewhat dystopian, but so is AI," he told the outlet in a text message. "The way the world works is changing." In another message he wrote, "We wanted something that would draw eyesyou don't draw eyes with boring messaging."So what does Artisan actually do? Its main product is an AI "sales agent" called Ava that supposedly automates the work of finding and messaging potential customers. The company claims it works with "no human input" and costs 96% less than hiring a human for the same role. Although, given the current state of AI technology, it's prudent to be skeptical of these claims.Artisan also has plans to expand its AI tools beyond sales into areas like marketing, recruitment, finance, and design. Its sales agent appears to be its only existing product so far.Meanwhile, the billboards remain visible throughout San Francisco, quietly fueling existential dread in a city that has already seen a great deal of tension since the pandemic. Some of the billboards feature additional messages, like "Hire Artisans, not humans," and one that plays on angst over remote work: "Artisan's Zoom cameras will never 'not be working' today."Benj EdwardsSenior AI ReporterBenj EdwardsSenior AI Reporter Benj Edwards is Ars Technica's Senior AI Reporter and founder of the site's dedicated AI beat in 2022. He's also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC. 123 Comments

Lisa Morgan, Freelance WriterDecember 10, 202410 Min ReadMyrarte via Alamy StockAs businesses grow and tech stacks become more complex, scalability remains a top issue.Companies face significant challenges scaling across both physical and virtual spaces. While a holistic approach to operations across regions provides advantages, it also introduces complexity, says Dustin Johnson, CTO of advanced analytics software provider Seeq. The cloud can assist, but its not always a one-size-fits-all solution, especially regarding compute needs. Specialized resources like GPUs for AI workloads versus CPUs for standard processes are essential, and technologies like Kubernetes allow for effective clustering and scaling. However, applications must be designed to fully leverage these features, or they wont realize the benefits.The variety of technologies involved creates significant complexity.Today, a vertically integrated tech stack isnt practical, as companies rely on diverse applications, infrastructure, AI/ML tools and third-party systems, says Johnson. Integrating all these components -- ensuring compatibility, security, and scalability -- requires careful coordination across the entire tech landscape.A common mistake is treating scalability as a narrow technology issue rather than a foundational aspect of system design. Approaching it with a short-term, patchwork mentality limits long-term flexibility and can make it difficult to respond to growing demands.Related:Following are some more things that need to scale better in 2025.1. ProcessesA lot of organizations still have manual processes that prevent velocity and scale. For example, if a user needs to submit a ticket for a new server to implement a new project, someone must write the ticket, someone receives the ticket, someone must activate it, and then something must be done with it. Its an entire sequence of steps.Thats not a scalable way to run your environment so I think scaling processes by leveraging automation is a really important topic, says Hillery Hunter, CTO and GM of innovation at IBM and an IBM Fellow. There are a bunch of different answers to that [ranging] from automation to what people talk about, such as is IT ops or orchestration technologies. If you have a CIO who is trying to scale something and need to get permission separately from the chief information security officers, the chief risk officer or the chief data officer team, that serialization of approvals blocks speed and scalability.Organizations that want to achieve higher velocities should make it a joint responsibility among members of the C-suite.Related:You dont just want to automate inefficient things in your organization. You really want to transform the business process, says Hunter. When you bring together the owners of IT, information, and security at the same table, you remove that serialization of the decision process, and you remove the impulse to say no and create a collective impetus to say yes because everyone understands the transformation is mutual and a team goal.2. IT operationsIT is always under pressure to deliver faster without sacrificing quality, but the pressure to do more with less leaves IT leaders and their staff overwhelmed.Scalability needs to be done though greater efficiency and automation and use things like AIOps to oversee the environment and make sure that as you scale, you maintain your security and resiliency standards, says Hunter. I think re-envisioning the extent of automation within IT and application management is not done until those processes break. Its maybe not investing soon enough so they can scale soon enough.3. ArchitecturesIn the interest of getting to market quickly, startups might be tempted to build a new service from existing pre-made components that can be coupled together in ways that mostly fit but will demonstrate the business idea. This can lead to unintentionally complicated systems that are impossible to scale because of their sheer complexity. While this approach may work well in the beginning, getting business approval later to completely re-architect a working service that is showing signs of success may be very difficult.Related:First of all, be very careful in the architectural phase of a solution [because] complexity kills. This is not just a reliability or security argument, it is very much a scalability argument, says Jakob stergaard, CTO at cloud backup and recovery platform Keepit. A complex structure easily leads to situations where one cannot simply throw hardware at the problem this can lead to frustrations on both the business side and the engineering side.He advises: Start with a critical mindset, knowing that upfront investment in good architecture will pay for itself many times over.4. Data visibilityOrganizations are on a constant mission to monetize data. To do that they need to actively manage that data throughout the entire lifecycle at scale.While cloud computing has gained popularity over the past few decades, there is still a lot of confusion, resulting in challenges including understanding where your cloud data lives, what it contains, and how to ensure it is properly protected, says Arvind Nithrakashyap, co-founder and CTO at data security company Rubrik. When it comes to scalability one blind spot is unstructured and semi-structured data.Unstructured data poses a security risk, as it can contain sensitive business data or personally identifiable information. And since all unstructured data is shared with end-user applications using standard protocols over TCP/IP networks, its a prime target for threat actors. Since most companies have hybrid and multi-cloud implementations IT needs to understand where sensitive data is, where it is going and how it is being secured.One of the toughest hurdles for organizations whose unstructured data portfolio includesbillions of files, and/or petabytes of data, is maintaining an accurate, up-to-date count ofthose datasets and their usage patterns, says Nithrakashyap. [You need to understand] things [such as] how many files [exist], where they are, how old they are, and whether theyre still in active use. Without reliable, up-to-date visibility into the full spectrum of critical business files, your organization can easily be overwhelmed by the magnitude of your data footprint, not knowing where critical datasets are located, which datasets are still growing, [and] which datasets have aged out of use.5. SaaS service APIsAPIs are the glue that holds our modern software-driven world together. Keepits stergaard says his company sees bottlenecks on software-as-a-service APIs that vendors offer up for general use, from explicit throttling to slow responses, that are outright intermittent failures. For better and tighter integrations between systems, APIs need to scale to higher volume use.Fundamentally, an API that does not scale is pointless, says stergaard. For APIs to be useful we want them to be usable. Not a little bit, not just sometimes, but all the time and as much as we need. Otherwise, what's the point?Although it can be difficult to pinpoint a limiting factor, if user experience is any indication, it appears that some services are built on architectures that are difficult for the vendor to scale to higher volume use.This is a classical problem in computer science -- if a service is built, for example, around a central database, then adding more API front-end nodes may not do anything to improve the scalability of the APIs because the bottleneck may be in the central database, says stergaard. If the system is built with a central database being core to its functionality, then replacing that central component with something that is better distributed over many systems could require a complete re-write of the service from the ground up. In practical terms for real world services, making a service scale to higher volume use is often very different from just clicking the elastic scaling button on the cloud platform on which it runs.To scale a solution, it must be built on the simplest possible architecture, since architectural complexity is typically the main obstacle to scaling a solution. A complex architecture can make throwing hardware at a solution completely ineffective.6. Artificial intelligenceAs AI usage accelerates, cloud and cybersecurity scalability become even more critical.[M]ost companies are still in a discovery phase [with AI], and therefore what it takes to scale [in terms of] capabilities, cost, etc. is still not fully understood. It requires an approach of continuous learning and experimentation, with a strong focus on outcomes, to prioritize the right activities, saysOrla Daly, CIO at digital workforce transformation company Skillsoft.IT leaders must ensure alignment with business leaders on the desired outcomes and critical success factors. They also need to understand the skills and resources in the organization, define KPIs and fill key gaps.Teams who are not proactively managing the need for scale will find suboptimal decisions or runaway costs on one side, or [a] lack of progress because the enablers and path to scale are not defined, says Daly. Scaling technology is ultimately about enabling business outcomes, therefore continuing to tie activities to the company priorities is important. Its easy to get carried away by new and exciting capabilities, and innovation remains important, but when it comes to scaling, its more important to take a thoughtful and measured approach.7. Generative AIOrganizations are struggling with scaling GenAI cost-effectively. Most providers bill for their models based on tokens that are numerical representations of words or characters. The costs for input and output tokens differ. For example, Anthropics Claude 3.5 Sonnet charges $3.00 per million input tokens and $15 per million output tokens while OpenAIs gpt-4o model costs $2.50 per million input tokens and $10 per million output tokens. The two models are not equal and support different features, so the choice isnt as clear cut as which model is cheaper.GenAI model consumers must pick a balance between price, capability and performance. Everyone wants the highest quality tokens at the lowest possible price as quickly as possible, says Randall Hunt, CTO at leading cloud services company and AWS Premier Tier Services partner, Caylent.An additional charge exists around vectorization of data, such as converting images, text, or other information into a numerical format, called an embedding, that represents the semantic meaning of the underlying data rather than the specific content.Embedding models are typically cheaper than LLMs. [For instance,] Coheres Embed English embedding model is $0.10 per million tokens. Embeddings can be searched somewhat efficiently using techniques like [hierarchical navigable small world](HNSW) and cosine similarity, which isnt important, but it requires the use of database extensions or specialized datastores that are optimized for those kinds of searches -- further increasing cost. [A]ll of this cost is additive, and it can affect the unit economics of various AI projects.8. Operational technologydataCompanies are being flooded with data. This goes for most organizations, but its especially true for industrial companies that are constantly collecting operational technology (OT) data from equipment, sensors, machinery and more. Industrial companies are eager to integrate insights from OT and IT data to enable data-driven decision making based on a holistic view of the business.In 2025 and beyond, companies that can successfully give data context and make efficient and secure connections between diverse OT and IT data sources, will be best equipped to scale data throughout the organization for the best possible outcomes, says Heiko Claussen, chief technology officer at industrial software company AspenTech. Point-to-point data connections can be chaotic and complex, resulting in siloes and bottlenecks that could make data less effective for agile decision making, enterprise-scale digital transformation initiatives and AI applications.Without OT data fabric, an organization that has 100 data sources and 100 programs utilizing those sources would need to write and maintain 10,000 point-to-point connections. With an OT data fabric, that drops to 200 connections. In addition, many of these connections will be based on the same driver and thus much easier to maintain and secure.About the AuthorLisa MorganFreelance WriterLisa Morgan is a freelance writer who covers business and IT strategy and emergingtechnology for InformationWeek. She has contributed articles, reports, and other types of content to many technology, business, and mainstream publications and sites including tech pubs, The Washington Post and The Economist Intelligence Unit. Frequent areas of coverage include AI, analytics, cloud, cybersecurity, mobility, software development, and emerging cultural issues affecting the C-suite.See more from Lisa MorganNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also LikeWebinarsMore WebinarsReportsMore Reports

Todays IT departments have an amalgamation of DevOps, Waterfall, artificial intelligence, and OS/new release software, so quality assurance must be able to test and to verify the goodness of all these variegated systems. Yet, those of us who have led IT departments know that the QA function is habitually under-appreciated.Understanding that QA must broaden its reach to test such a broad spectrum of different systems, vendors have rolled out QA tools like the automated execution of test scripts that QA designs.This has generated a steady market in QA testing software, which Global Market Insights pinpointed at $51.8 billion in 2023, with a projected CAGR (compound annual growth rate) of 7% between 2024 and 2032.What IT departments should do now is strategize how a limited QA staff can best use these tools, while also developing the knowledge base and reach allowing them to cover the broad array of new applications and systems that QA is being asked to test.Performing QA With No Single Pane of GlassIf you are in system programming or network support, you know that there are over-arching software solutions that boast single pane of glass visibility. These systems provide an overall architecture that enables you to unify visibility of all of the different tools and functions that you have on a single screen. Not all IT departments invest in these expensive software architectures, but at least they do exist.Related:That isnt the case for quality assurance.In QA, the test bench is a hodgepodge of different tools and techniques spread out on a general tool bench. When a staffer performs QA, they pick whatever tools they choose to use from this tool bench based upon the type of application they are being called upon to test.If the application area to be tested is DevOps, QA is an iterative never done function that might use some test automation for workflow execution, but that also requires a high amount of collaboration between QA, development and end users until everyone arrives at a consensus that the application is production ready.In the AI environment, testing is also iterative and never finished. You work with development and user area subject matter experts to achieve the gold standard of 95% accuracy with what subject matter experts would conclude. Then you must periodically reaffirm accuracy because business conditions constantly change, and accuracy levels could fall.If the application is waterfall, it routes through the traditional path of development, unit test, integration test, regression test, deploy.Related:If the system is a new database or operating or infrastructure system release from a vendor, the new release is first simulated in a test environment, where it is tested and debugged. The new release gets installed into production when all testing issues in the simulated environment are resolved.Each of these test scenarios requires a different mental approach to QA and a different set of tools.Make QA a Strategic Function and Elevate its Standing?Test tool provider Hatica has stated,In the past, QA engineers were primarily focused on testing -- finding bugs and ensuring that the product worked as intended before it was released to users. However, this reactive approach to quality is no longer enough in todays environment. Before long, QA engineers will shift from being testers at the end of the process to quality strategists who are involved from the very beginning.In Agile and DevOps development, there already is an emerging trend for QA that confirms this. QA is immediately engaged in Agile and DevOps work teams, and the QA team provides as much input into the end-to-end DevOps/Agile process as development and end users. As IT departments move more work to Agile and DevOps, QAs role as a frontend strategist will expand.Related:However, in waterfall and new infrastructure release deployments, QAs role is more backend and traditional. It performs end of the line checkouts and is often not engaged in the initial stages of development. AI also presents a QA challenge, because a separate data science or subject matter expert group might do most of the system development and checkout, so QAs role is minimized.The Best Approach to QAThanks to the Agile/DevOps movement, QA now sees a more forward-thinking and strategic role. Yet at the same time, applications in the AI, waterfall, and infrastructure areas engage QA as more of a backend function.QA is also knee-capped by the lack of a single architecture for its tools, and by the brutal fact that most of the staff in QA departments are new hires or junior personnel. Quickly, these individuals apply for transfers into application development, database or systems, because they see these as the only viable options for advancing their IT careers.Understanding these realities, CIOs can do three things:1. Move QA into a more strategic position in all forms of application development. Like the IT help desk, QA has a long institutional memory of the common flaws in IT applications. If QA is engaged early in application development processes, it can raise awareness of these common flaws so they can be addressed up front in design.Accept as well that most QA staff members will want to move on to become a developer or an IT technical specialist and use QA as a grooming ground. To this end, the more QA gets engaged early in application planning and development, the more IT software knowledge QA staff will gain. This can prepare them for development or systems careers, if they choose to take these routes later.2. Ensure that QA staff is properly trained on QA tools. There is no uber architecture available for the broad assortment of tools that QA uses, so personalized training is key.3. Foster collaboration. In the Agile/DevOps environment, there is active collaboration between QA, development and end users. In AI development, CIOs can foster greater QA collaboration by teaming QA with IT business analysts, who often work side by side with user subject matter experts and data scientists. In new infrastructure release testing and in waterfall testing, more active collaboration should be fostered with system and application programmers.The more collaborative bridges you build, the more effectively your QA function will perform.