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Exploring Early ’90s Video Game Architecture With Another World

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Curious about past computer architectures? Software engineer [Fabien Sanglard] has been experimenting with porting Another World, an action-adventure platformer, to different machines and comparing the results in his “Polygons of Another World” project.

The results are pretty interesting. Due to the game’s polygon-based graphics, optimizations vary widely across different architectures, with tricks allowing the software to run on hardware released five years before the game’s publication. The consoles explored are primarily from the early ’90s, ranging from the Amiga 500, Atari ST, IBM PC, and Super Nintendo to the Sega Genesis.

The actual game contains very little code, with the original version at 6000 lines of assembly and the PC DOS executable only containing 20 KiB. The executable simply exists as a virtual machine host that reads and executes uint8_t opcodes, with most of the business logic implemented with bytecode. The graphics use 16 palette-based colors, despite the Amiga 500 supporting up to 32 colors. However, the aesthetics still fit the game nicely, with some very pleasant pixel art.

There’s a plethora of cool tricks that emerge in each of the ports, starting with the original Amiga 500 execution. Prior to the existence of the CPU/GPU architecture, microprocessors had blitters – logic blocks that rapidly modified data within the memory, capable of copying large swathes of data in parallel with the CPU, freeing up the CPU for other operations.

To display the visuals, a framebuffer containing a bitmap drives the display. There are three framebuffers used, two for double buffering and one for saving the background composition to avoid redrawing static polygons. Within the framebuffer, several tricks are used to improve the graphical experience. For scenes with translucent hues, special values are interpreted from the framebuffer index by “reading the framebuffer index, adding 0x8 and writing back”.

Challenges also come when manipulating pixels given each machine’s CPU and bus bandwidth limitations. For filling in bits, the blitter uses a feature called “Area Fill Mode” that scans left to right to find edges, rendering the bit arrays with spaces between lines filled in. Since the framebuffer is stored in five separate areas of memory – or bitplanes – this requires drawing the lines and filling in areas four times, multiplying by the hundreds of polygons rendered by the engine. The solution was to set up a temporary “scratchpad” buffer and rendering a polygon into the clean space. The polygon can then get copied to the screen area with a masked blit operation since the blitter can render anywhere in memory.

Intrigued? The series continues with deep dives into Atari ST, IBM PC, and upcoming writeups on SEGA Genesis/MegaDrive.



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Fossil discovery shows how ancient ‘hell ants’ hunted with metal headgear

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Researchers discover the fossil of a ‘hell ant’ preserved in amber. (Credits: NJIT / SWNS)

A new fossil discovery shows how ancient ‘hell ants’ hunted with metal headgear and vertically-grasping pincers.

The 99-million-year-old amber fossil has pristinely preserved the hellish predator as it embraced its unsuspecting final victim, an ancient relative of the cockroach.

The ancient encounter recovered from Myanmar, offers a detailed glimpse at how the prehistoric hell ants once used their killer features to exterminate prey.

It also reveals vital information about how the evolutionary process enabled the ants to accrue their remarkable killing kits.

Perhaps at the pinnacle of its hellish armoury were deadly, scythe-like mandibles which operated in a vertical motion to pin prey against their long horns.

Among the recently-identified ants is a species named Linguamyrmex vladi, or ‘Vlad the Impaler’ by Dr Phillip Barden and his colleagues in 2017.

The 16 species of hell ants evolved their jaw dropping head and mouth weaponry in an integrated process helping them to trap their ancient prey, without hurting themselves.

The researchers say the earliest hell ant ancestors would have first gained the ability to move their mouthparts vertically.

This, in turn, would integrate the mouthparts and head in a way that was unique to this extinct lineage.

Dr Barden, of New Jersey Institute of Technology, US, said: ‘Integration is a powerful shaping force in evolutionary biology… when anatomical parts function together for the first time, this opens up new evolutionary trajectories as the two features evolve in concert.’

He added: ‘The consequences of this innovation in mouthpart movement with the hell ants are remarkable.’

Vlad the Impaler, discovered by Barden and colleagues in 2017, was thought to have used a metal-reinforced horn on its head to impale prey — a trait potentially used to feed on the internal liquid (hemolymph) of insects.

He continued: ‘While no modern ants have horns of any kind, some species of hell ant possess horns coated with serrated teeth, and others like Vlad are suspected to have reinforced its horn with metal to prevent its own bite from impaling itself.’

The ancient fossil recovered from Myanmar, offers a detailed glimpse at how the prehistoric hell ants once used their killer features to exterminate prey. (Credits: NJIT / SWNS)

Researchers say the rare fossil demonstrating the hell ant’s feeding mode offers a possible explanation for its unusual morphology.

They also said the finding highlights a key difference between some of the earliest ant relatives and their modern counterparts, which all feature mouthparts that grasp laterally.

The hell ant lineage are suspected to have vanished along with many other early ant groups during periods of ecological change around 65 million years ago.

Dr Barden added: ‘Fossilised behaviour is exceedingly rare, predation especially so.

‘As palaeontologists, we speculate about the function of ancient adaptations using available evidence, but to see an extinct predator caught in the act of capturing its prey is invaluable.’

‘This fossilised predation confirms our hypothesis for how hell ant mouthparts worked

‘The only way for prey to be captured in such an arrangement is for the ant mouthparts to move up and downward in a direction unlike that of all living ants and nearly all insects.’

Since the first hell ant was unearthed about a hundred years ago, it’s been a mystery to biologists as to why these extinct animals are so distinct from today’s ants.

Dr Barden said: ‘This fossil reveals the mechanism behind what we might call an ‘evolutionary experiment,’ and although we see numerous such experiments in the fossil record, we often don’t have a clear picture of the evolutionary pathway that led to them.’

To explore further, the researchers compared the head and mouthpart of hell ants with similar datasets of living and fossil ant species.

The team also conducted an analysis to reconstruct evolutionary relationships among both extinct and modern ants.

Their probe confirmed that hell ants belong to one of the earliest branches of the ant evolutionary tree and are each other’s closest relatives.

Moreover, the relationship between mandible and head morphology is unique in hell ants compared to living lineages due to their specialised methods for capturing prey.

The fossil has finally provided Dr Barden’s lab with firmer answers as to how this long-lost class of ant predators reigned for nearly 20 million years.

But questions persist, such as what led these and other lineages to go extinct while modern ants flourished into the common insects we know today.

The team is now seeking to describe species from new fossil deposits to learn more about how extinction impacts groups differently.

Dr Barden added: ‘Over 99 per cent of all species that have ever lived have gone extinct.

‘As our planet undergoes its sixth mass extinction event, it’s important that we work to understand extinct diversity and what might allow certain lineages to persist while others drop out.

‘I think fossil insects are a reminder that even something as ubiquitous and familiar as ants have undergone extinction.’

The findings were published in the journal Current Biology.



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Microsoft Abandons Project xCloud Game Streaming on iOS

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Microsoft’s upcoming game streaming service, Project xCloud, will allow you to play games in the cloud no matter where you are. However, for some unknown reason, Microsoft has abandoned testing xCloud on iOS. And the company is instead focusing on an Android-only release.

What Happened With Project xCloud on iOS?

Microsoft opened its doors for iOS testers back in early 2020. Microsoft had previously told users that testing would continue until September 11, 2020; however, the company has since announced that iOS testing will end on August 5. The planned Android test dates did not change; neither did its release date of September 15, 2020.

In a statement to The Verge, A Microsoft representative said:

“Our Project xCloud preview TestFlight period has ended on iOS and we are focused on delivering cloud gaming as part of Xbox Game Pass Ultimate to Android customers beginning September 15. It’s our ambition to scale cloud gaming through Xbox Game Pass available on all devices.”

Why Has Microsoft Killed Project xCloud on iOS?

Microsoft has not make an official statement explaining why it has abandoned iOS in favor of Android. However, there are a few reasons which hint as to how Microsoft arrived at this decision.

First, testing Project xCloud on iOS did not go smoothly. Due to the iOS App Store policy, Microsoft could only allow 10,000 users to test the service. Not only that, but this small pool of testers could only test the game, Halo: The Master Chief Edition. As a result, Microsoft probably could not test the iOS app to a satisfactory level, thus prompting the company to drop support for it.

If this theory is correct, Microsoft is not the first company to suffer issues launching on iOS. Google’s game streaming service, Stadia, has still not launched on iOS devices. The Steam Link app took a year to release after Valve fought to meet Apple’s high standards. As such, this may be another story of a games company struggling to launch on the iOS App Store.

However, Microsoft made an appearance at the Samsung Galaxy Unpacked 2020 event. During the event, Samsung mentioned how close the company has worked with Microsoft to bring Project xCloud to Galaxy phones. While the Project xCloud presentation did not show any Samsung-exclusive features, the partnership may have forced Microsoft to stop its iOS support to favor Android instead. But that is pure speculation.

Preparing for the Launch of Project xCloud

With the launch of Project xCloud rapidly approaching, Microsoft has stopped testing on iOS to focus on an Android-only release. Whether this is because Microsoft encountered issues with Apple’s App Store policies, or because its Samsung partnership has muddied the waters, is as-yet unknown.

If you’re unsure about how gaming in the cloud works, be sure to read our explainer detailing how cloud gaming works.

Read the full article: Microsoft Abandons Project xCloud Game Streaming on iOS



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The pandemic has changed how criminals hide their cash—and AI tools are trying to sniff it out

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When economies across the world shut down earlier this year, it wasn’t only business owners and consumers who had to adapt. Criminals suddenly had a problem on their hands. How to move their money?

Profits from organized crime are typically passed through legitimate businesses, often exchanging hands several times and crossing borders, until there is no clear trail back to its source—a process known as money laundering.

But with many businesses closed, or seeing smaller revenue streams than usual, hiding money in plain sight by mimicking everyday financial activity became harder. “The money is still coming in but there’s nowhere to put it,” says Isabella Chase, who works on financial crime at RUSI, a UK-based defense and security think tank.

The pandemic has forced criminal gangs to come up with new ways to move money around. In turn, this has upped the stakes for anti-money laundering (AML) teams tasked with detecting suspicious financial transactions and following them back to their source.

Key to their strategies are new AI tools. While some larger, older financial institutions have been slower to adapt their rule-based legacy systems, smaller, newer firms are using machine learning to look out for anomalous activity, whatever it might be.

It is hard to assess the exact scale of the problem. But according to the United Nations Office on Drugs and Crime, between 2% and 5% of global GDP—between $800 billion and $2 trillion at current figures—is laundered every year. Most goes undetected. Estimates suggest that only around 1% of profits earned by criminals is seized.

And that was before covid-19 hit. Fraud is up, with fears around covid-19 creating a lucrative market for counterfeit protective gear or medication. More people spending time online also creates a bigger pool for phishing attacks and other scams. And, of course, drugs are still being bought and sold.

Lockdown made it harder to hide the proceeds—at least to begin with. The problem for criminals is that many of the best businesses for laundering money were also those hit hardest by the pandemic. Small shops, restaurants, bars, and clubs are favored because they are cash-heavy, which makes it easier to mix up ill-gotten gains with legal income.

With bank branches closed, it has been harder to make large cash deposits. Wire transfer services like Western Union—which usually allow anyone to walk in off the street and send money overseas—shut their premises, too.

But criminals are nothing if not opportunistic. As the normal channels for money laundering closed, new ones opened up. Vast sums of money have started flowing into small businesses again thanks to government bailouts. This creates a flurry of financial activity that provides cover for money laundering.

Breaking the rules

The upshot is that there are more demands being placed on AML tech. Older systems rely on hand-crafted rules, such as that transactions over a certain amount should raise an alert. But these rules lead to many false flags and real criminal transactions get lost in the noise. More recently, machine-learning based approaches try to identify patterns of normal activity and raise flags only when outliers are detected. These are then assessed by humans, who reject or approve the alert.

This feedback can be used to tweak the AI model so that it adjusts itself over time. Some firms, including Featurespace, a firm based in the US and UK that uses machine learning to detect suspicious financial activity, and Napier, another firm that builds machine learning tools for AML, are developing hybrid approaches in which correct alerts generated by an AI can be turned into new rules that shape the overall model.  

The rapid shifts in behavior in recent months have made the advantages of more adaptable systems clear. Financial regulators around the world have released new guidance on what sort of activity AML teams should look out for but for many it was too late, says Araliya Sammé, head of financial crime at Featurespace. “When something like covid happens, where everybody’s payment patterns change suddenly, you don’t have time to put new rules in place.”

You need tech that can catch it as it is happening, she says: “Otherwise by the time you’ve detected something and alerted the people who need to know, the money is gone.” 

For Dave Burns, chief revenue officer for Napier, covid-19 caused long-simmering problems to boil over. “This pandemic was the tipping point in many ways,” he says. “It’s a bit of a wake-up call that we really need to think differently.” And, he adds, “some of the larger players in the industry have been caught flat-footed.”

But that doesn’t simply mean adopting the latest tech. “You can’t just do AI for AI’s sake because that will spew out garbage,” says Burns. What’s needed, he says, is a bespoke approach for each bank or payment provider.

AML technology still has a long way to go. The pandemic has revealed cracks in existing systems that have people worried, says Burns. And that means that things could change faster than they were going to. “We’re seeing a greater degree of urgency,” he says. “What is traditionally very long, bureaucratic decision-making is being accelerated dramatically.”



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