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Nikon Z 40mm f/2 review: this cheap, modern ‘nifty forty’ has been my every day lens for over a year and it hasn’t let me down

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Two-minute review

Nikon’s Nikkor Z 40mm f/2 is one of two lightweight, inexpensive prime lenses for the Z-mount – the other being the wider 28mm f/2.8. 

At 40mm, it’s currently the closest match to the ‘nifty fifty’ lenses of old, aiming to provide a lightweight lens with a compact footprint, flexible focal length, and a relatively fast aperture. Above all, it’s cheap – really cheap for a proprietary lens sitting at just £259 / $289 /AU$310 new. Compared to the Nikon S 50mm f/1.8 or the S 35mm f/1.8, the 40mm comes in at under half the price while still offering some form of weather sealing and excellent performance.

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News

Spotify Complains That Apple Hasn’t Approved Update With Subscription Pricing and Links in EU

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Apple has not approved a Spotify app update that adds information on subscription pricing and links its website, Spotify complained today in an email to the European Commission (via The Verge). Spotify says that Apple has not “acknowledged nor responded” to its App Store submission.

Apple vs Spotify feature2
The European Commission on March 4 fined Apple almost $2 billion and said that Apple abused its dominant position in the market by preventing music streaming services from telling users about more affordable subscription prices outside of their iOS apps. The EC said that it is “illegal under EU antitrust rules” for Apple to keep developers from telling customers about cheaper music subscription options.

Apple was told that it must “remove anti-steering provisions” in the European Union, and so on March 5, Spotify submitted an app update that included subscription pricing tiers and options to pay without using in-app purchase. Spotify says that it has not had a response from Apple since submitting the update.

Spotify told the European Commission that Apple’s lack of response is “yet another example” of how Apple “will seek to circumvent and/or not comply with the Commission’s decision.” Spotify asked the EC to require Apple to approve the app update.

In a statement to The Verge, Spotify also said that Apple’s delay “directly conflicts” with Apple’s statements about processing app submissions within 24 hours, and “flies in the face of the timeline for adoption” from the EC.

It’s been nine days now and we’re still waiting to hear from Apple about our app submission to show EU consumers pricing and a link to our website, which we are now authorized to do by the European Commission’s decision on the music streaming case. Apple’s delay directly conflicts with their claim that they turn around reviews on app submissions within 24 hours, and it also flies in the face of the timeline for adoption the Commission laid out.

The ruling from the European Commission that requires Apple to eliminate anti-steering rules is separate from the app ecosystem changes that Apple made in the European Union with iOS 17.4 to comply with the Digital Markets Act (DMA).

Under the terms of the DMA, Spotify is allowed to distribute a Spotify app to EU users outside of the ‌App Store‌, but it would be required to pay Apple’s Core Technology Fee for each user. Spotify currently does not pay Apple any commission.

The DMA also permits Spotify to direct users to make purchases on its website while also providing information on in-app promotions, discounts, and deals, but again, Spotify would need to agree to Apple’s updated business terms and fees to implement these changes. Spotify has not clarified if it adopted Apple’s new terms or if its update has been submitted without doing so.

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Entertainment

Google DeepMind’s new AI can follow commands inside 3D games it hasn’t seen before

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has unveiled new research highlighting an AI agent that’s able to carry out a swath of tasks in 3D games it hasn’t seen before. The team has long been experimenting with AI models that can win in the likes of and chess, and even learn games . Now, for the first time, according to DeepMind, an AI agent has shown it’s able to understand a wide range of gaming worlds and carry out tasks within them based on natural-language instructions.

The researchers teamed up with studios and publishers such as Hello Games (), Tuxedo Labs () and Coffee Stain ( and ) to train the Scalable Instructable Multiworld Agent (SIMA) on nine games. The team also used four research environments, including one built in Unity in which agents are instructed to form sculptures using building blocks. This gave SIMA, described as “a generalist AI agent for 3D virtual settings,” a range of environments and settings to learn from, with a variety of graphics styles and perspectives (first- and third-person).

“Each game in SIMA’s portfolio opens up a new interactive world, including a range of skills to learn, from simple navigation and menu use, to mining resources, flying a spaceship or crafting a helmet,” the researchers wrote in a blog post. Learning to follow directions for such tasks in video game worlds could lead to more useful AI agents in any environment, they noted.

A flowchart detailing how Google DeepMind trained its SIMA AI agent. The team used gameplay video and matched that to keyboard and mouse inputs for the AI to learn from.

Google DeepMind

The researchers recorded humans playing the games and noted the keyboard and mouse inputs used to carry out actions. They used this information to train SIMA, which has “precise image-language mapping and a video model that predicts what will happen next on-screen.” The AI is able to comprehend a range of environments and carry out tasks to accomplish a certain goal.

The researchers say SIMA doesn’t need a game’s source code or API access — it works on commercial versions of a game. It also needs just two inputs: what’s shown on screen and directions from the user. Since it uses the same keyboard and mouse input method as a human, DeepMind claims SIMA can operate in nearly any virtual environment.

The agent is evaluated on hundreds of basic skills that can be carried out within 10 seconds or so across several categories, including navigation (“turn right”), object interaction (“pick up mushrooms”) and menu-based tasks, such as opening a map or crafting an item. Eventually, DeepMind hopes to be able to order agents to carry out more complex and multi-stage tasks based on natural-language prompts, such as “find resources and build a camp.”

In terms of performance, SIMA fared well based on a number of training criteria. The researchers trained the agent in one game (let’s say Goat Simulator 3, for the sake of clarity) and got it to play that same title, using that as a baseline for performance. A SIMA agent that was trained on all nine games performed far better than an agent that trained on just Goat Simulator 3.

Chart showing hte relative performance of Google DeepMind's SIMA AI agent based on varying training data.

Google DeepMind

What’s especially interesting is that a version of SIMA that was trained in the eight other games then played the other one performed nearly as well on average as an agent that trained just on the latter. “This ability to function in brand new environments highlights SIMA’s ability to generalize beyond its training,” DeepMind said. “This is a promising initial result, however more research is required for SIMA to perform at human levels in both seen and unseen games.”

For SIMA to be truly successful, though, language input is required. In tests where an agent wasn’t provided with language training or instructions, it (for instance) carried out the common action of gathering resources instead of walking where it was told to. In such cases, SIMA “behaves in an appropriate but aimless manner,” the researchers said. So, it’s not just us mere mortals. Artificial intelligence models sometimes need a little nudge to get a job done properly too.

DeepMind notes that this is early-stage research and that the results “show the potential to develop a new wave of generalist, language-driven AI agents.” The team expects the AI to become more versatile and generalizable as it’s exposed to more training environments. The researchers hope future versions of the agent will improve on SIMA’s understanding and its ability to carry out more complex tasks. “Ultimately, our research is building towards more general AI systems and agents that can understand and safely carry out a wide range of tasks in a way that is helpful to people online and in the real world,” DeepMind said.

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