Technology

Now that I’ve finally played The Last of Us, who wants to talk about that ending? | Games

‘OK, Dad, this is an incredible essay on the effects of grief and grey morality in a postapocalyptic society,” says the eldest child, AKA the millennial. “It’s got proper female characters, progressive takes on sexuality and tonnes of rain.”

“They’ve made a video game of The Handmaid’s Tale?”

“No, Dad. It’s The Last of Us. Don’t worry. It’s still a zombie shooter. And both games have the best ending ever.”

Now she has my interest. Video game endings fascinate me, because my generation started out with arcade games that didn’t have them. Pac-Man kept eating dots and chasing ghosts and the Space Invaders kept coming, wave after incessant wave. The first arcade game that had an actual ending was Dragon’s Lair and nobody actually saw that because it was so hard to complete.

I have a tough start with The Last of Us because I hate games where you search for stuff in every room of a house. I spend my normal life doing that with car keys and headphones. I want games where you walk into a room and all the objects get sucked into a magic pocket. But that isn’t realistic, I hear you cry. Well, neither is only being able to carry three shivs in a world where, despite the zombie apocalypse, cargo pants clearly still exist.

I also hate any form of crafting, because that was what my generation had to do for “fun” as kids before we had video games. Whether it’s smoke bombs from sugar and explosives or a set of Action Man drawers from matchboxes, it’s all boring to me.

“Keep going,” I tell myself. “The millennial says it’s got the best ending ever.”

Throughout the first chapter of Joel and Ellie’s jaunt across a post-infected US I keep trying to guess what this great ending will be. Maybe Ellie isn’t immune to infection after all? Maybe Joel is her real father? Maybe they’re both unwitting participants in some reality TV show, I’m Infected Get Me Out of Here?

As you will all know by now – and if you’ve yet to play The Last of Us then please stop reading – the ending has Joel murder a perfectly innocent and well-intentioned doctor who wants to cut Ellie open to find a cure that will save humanity. But Joel has no truck with utilitarian philosophy, because Ellie has now become a replacement for the daughter he lost. So, he disregards mankind’s future and, by stopping the operation, effectively murders the entire human race (alongside a whole hospital’s worth of doctors).

“Why does he do that?” I asked the millennial, in one of many fantastic discussions we had about the game.

“Because he’s a white male,” came the answer, because it’s 2022 and she’s in her 20s. And maybe she’s right. Either way it is a jaw-dropping, supremely brave ending and the terrific Left Behind side-story also brought the feels.

So, when it came to The Last of Us Part 2, I was beyond excited. Fifty million hours later I was beyond disappointed.

Don’t get me wrong, the millennial nailed it when she said it was a great exploration of the effects of grief and grey morality. But after spending the whole game switching between two strong female characters (literally, have you seen Abby’s arms?) and contrasting factional creeds, you have the final confrontation. They fight. And … they both live. And go their separate ways. The only real damage is Ellie losing a couple of fingers, and the game portrays the worst consequence of this as not being able to play guitar any more. Seriously? That’s the biggest drawback to being fingerless in a zombie apocalypse? The first game ended with Joel murdering an entire civilisation, the second ends with Ellie murdering one song on a guitar. It’s a scene you might have found in The Secret of Monkey Island. It’s hilarious.

The Last of Us Part 2 leaves us with exactly the same non-ending as those original arcade games. Ellie and Abby will go on killing to keep their respective postapocalyptic factions going, both driven by the grief of murdered loved ones. They are both trapped, endlessly chasing ghosts. Sounds familiar…

The millennial says this shows there are no winners when it comes to revenge. I say they want both protagonists alive for The Last of Us 3. It’s a cynical cop out. But then, The Last of Us Part 2 is a game that features the most cynical scene ever, where apropos of nothing, after genuinely bravura portrayals of women, transgender and gay characters, alpha female Abby suddenly gets rogered from behind by some guy. It happens out of nowhere. The game spends umpteen hours portraying progressive sexuality, and then it’s like some marketing man decided they needed to toss the incels a piece of red meat to stop them hate-bombing all over 4chan (which didn’t work). It is easily the most gratuitous bit of nudity I have ever seen in games, and I have played The Witcher 3. The rogerer in question even has a girlfriend. Who is pregnant. Way to shit on a sister, Abby.

“It’s basically Pac-Man with gratuitous boobs,” I say to my eldest, who sighs and pours herself a large cup of coffee. This will be another long discussion.

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Typo blamed for Microsoft Azure DevOps outage in Brazil • The Register

Microsoft Azure DevOps, a suite of application lifecycle services, stopped working in the South Brazil region for about ten hours on Wednesday due to a basic code error.

On Friday Eric Mattingly, principal software engineering manager, offered an apology for the disruption and revealed the cause of the outage: a simple typo that deleted seventeen production databases.

Mattingly explained that Azure DevOps engineers occasionally take snapshots of production databases to look into reported problems or test performance improvements. And they rely on a background system that runs daily and deletes old snapshots after a set period of time.

During a recent sprint – a group project in Agile jargon – Azure DevOps engineers performed a code upgrade, replacing deprecated Microsoft.Azure.Managment.* packages with supported Azure.ResourceManager.* NuGet packages.

The result was a large pull request of changes that swapped API calls in the old packages for those in the newer packages. The typo occurred in the pull request – a code change that has to be reviewed and merged into the applicable project. And it led the background snapshot deletion job to delete the entire server.

“Hidden within this pull request was a typo bug in the snapshot deletion job which swapped out a call to delete the Azure SQL Database to one that deletes the Azure SQL Server that hosts the database,” said Mattingly.

Azure DevOps has tests to catch such issues, but according to Mattingly, the errant code only runs under certain conditions and thus isn’t well covered under existing tests. Those conditions, presumably, require the presence of a database snapshot that is old enough to be caught by the deletion script.

Mattingly said Sprint 222 was deployed internally (Ring 0) without incident due to the absence of any snapshot databases. Several days later, the software changes were deployed to the customer environment (Ring 1) for the South Brazil scale unit (a cluster of servers for a specific role). That environment had a snapshot database old enough to trigger the bug, which led the background job to delete the “entire Azure SQL Server and all seventeen production databases” for the scale unit.

The data has all been recovered, but it took more than ten hours. There are several reasons for that, said Mattingly.

One is that since customers can’t revive Azure SQL Servers themselves, on-call Azure engineers had to handle that, a process that took about an hour for many.

Another reason is that the databases had different backup configurations: some were configured for Zone-redundant backup and others were set up for the more recent Geo-zone-redundant backup. Reconciling this mismatch added many hours to the recovery process.

“Finally,” said Mattingly, “Even after databases began coming back online, the entire scale unit remained inaccessible even to customers whose data was in those databases due to a complex set of issues with our web servers.”

These issues arose from a server warmup task that iterated through the list of available databases with a test call. Databases in the process of being recovered chucked up an error that led the warm-up test “to perform an exponential backoff retry resulting in warmup taking ninety minutes on average, versus sub-second in a normal situation.”

Further complicating matters, this recovery process was staggered and once one or two of the servers started taking customer traffic again, they’d get overloaded, and go down. Ultimately, restoring service required blocking all traffic to the South Brazil scale unit until everything was sufficiently ready to rejoin the load balancer and handle traffic.

Various fixes and reconfigurations have been put in place to prevent the issue from recurring.

“Once again, we apologize to all the customers impacted by this outage,” said Mattingly. ®

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What are the current trends in Ireland’s pharma sector?

SiliconRepublic.com took a look at PDA Ireland’s Visual Inspection event to learn about Ireland’s pharma sector and its biggest strengths.

Ireland’s pharmaceutical stakeholders gathered in Cork recently to learn the latest developments and regulatory changes in the sector.

The event was hosted by the Irish chapter of the Parenteral Drug Association (PDA), a non-profit trade group that shares science, technology and regulatory information to pharma and biopharma companies.

The association held a Visual Inspection event in Cork last month, where speakers shared their outlooks on the industry, the regulatory landscape and tips on product investigation.

PDA Ireland committee member Deidre Tobin told SiliconRepublic.com that one goal of the event was to get bring the industry together and help SMEs engage with top speakers.

“The mission of PDA is really to bring people together in industry and to have that network sharing, that information gathering so that we’re all consistent, we all have the same message,” Tobin said.

Ireland’s advantages

Ireland has grown to become a hub of leading pharma companies over the years, with many multinational companies setting up sites here. By 2017, 24 of the world’s top biotech and pharma companies had made a home for themselves in Ireland.

The sector also remains active in terms of merger and acquisition deals. A William Fry report claimed Pharma accounted for 12pc of all Irish M&A deals by volume in 2022.

Ruaidhrí O’Brien, head of UK and Ireland sales at Körber Pharma and a PDA Ireland member, said the country has a “wealth of experience” across various types of pharmaceutical production, such as API bulk and solid dosage production.

O’Brien claimed there’s also been growth in the “liquid fill finish area”, which relates to completed pharma products such as vaccines. During the Covid-19 pandemic, Pfizer confirmed its Irish operations were being used to manufacture its vaccine.

O’Brien also said Ireland has “skilled people” that are in senior levels within companies, which he feels is why existing companies continue to invest and why “we have amazing investments from all the global leaders”.

Regulatory changes

One speaker at the PDA Ireland Visual Inspection event was John Shabushnig, the founder of Insight Pharma Consulting LLC. He spoke about current and upcoming regulation impacting the global sector.

Shabushnig said he sees the overall industry understanding of what it can and can’t do “continuing to improve”. He also said there is better alignment between regulators and industry now “than I saw 10 or 20 years ago”.

Shabushnig spoke positively about the regulatory landscape overall and couldn’t think of any “big misses” in terms of industry ignoring regulation. But he did note that some developing areas in the industry are “a bit unknown”.

“Advanced therapies, cell and gene therapies, there are some unique challenges on inspecting those products that we’re kind of learning together at this point,” Shabushnig said.

But Shabushnig said there are also “big opportunities” ahead with new tools that can be taken advantage of. One example he gave was using AI for automated visual inspection, which Shabushnig described as a “very exciting tool”.

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Explaining AI Black Box

By Prof Saurabh Bagchi

Prof Saurabh Bagchi from Purdue University explains the purpose of AI black boxes and why researchers are moving towards ‘explainable AI’.

For some people, the term ‘black box’ brings to mind the recording devices in airplanes that are valuable for postmortem analyses if the unthinkable happens. For others, it evokes small, minimally outfitted theatres. But ‘black box’ is also an important term in the world of artificial intelligence.

AI black boxes refer to AI systems with internal workings that are invisible to the user. You can feed them input and get output, but you cannot examine the system’s code or the logic that produced the output.

Machine learning is the dominant subset of artificial intelligence. It underlies generative AI systems like ChatGPT and DALL-E 2. There are three components to machine learning: an algorithm or a set of algorithms, training data and a model.

An algorithm is a set of procedures. In machine learning, an algorithm learns to identify patterns after being trained on a large set of examples – the training data. Once a machine-learning algorithm has been trained, the result is a machine-learning model. The model is what people use.

For example, a machine-learning algorithm could be designed to identify patterns in images and the training data could be images of dogs. The resulting machine-learning model would be a dog spotter. You would feed it an image as input and get as output whether and where in the image a set of pixels represents a dog.

Any of the three components of a machine-learning system can be hidden, or in a black box. As is often the case, the algorithm is publicly known, which makes putting it in a black box less effective. So, to protect their intellectual property, AI developers often put the model in a black box. Another approach software developers take is to obscure the data used to train the model – in other words, put the training data in a black box.

The opposite of a black box is sometimes referred to as a glass box. An AI glass box is a system whose algorithms, training data and model are all available for anyone to see. But researchers sometimes characterise aspects of even these as black box.

That’s because researchers don’t fully understand how machine-learning algorithms, particularly deep-learning algorithms, operate. The field of explainable AI is working to develop algorithms that, while not necessarily glass box, can be better understood by humans.

Thinking Outside The Black Box

In many cases, there is good reason to be wary of black box machine-learning algorithms and models. Suppose a machine-learning model has made a diagnosis about your health. Would you want the model to be black box or glass box? What about the physician prescribing your course of treatment? Perhaps she would like to know how the model arrived at its decision.

What if a machine-learning model that determines whether you qualify for a business loan from a bank turns you down? Wouldn’t you like to know why? If you did, you could more effectively appeal the decision, or change your situation to increase your chances of getting a loan the next time.

Black boxes also have important implications for software system security. For years, many people in the computing field thought that keeping software in a black box would prevent hackers from examining it and therefore it would be secure. This assumption has largely been proven wrong because hackers can reverse engineer software – that is, build a facsimile by closely observing how a piece of software works – and discover vulnerabilities to exploit.

If software is in a glass box, software testers and well-intentioned hackers can examine it and inform the creators of weaknesses, thereby minimising cyberattacks.

By Prof Saurabh Bagchi

Saurabh Bagchi is professor of electrical and computer engineering and director of corporate partnerships in the School of Electrical and Computer Engineering at Purdue University in the US. His research interests include dependable computing and distributed systems.