New weather conditions blanket above-ground habitats.
The below zero temperatures of this arctic region pose a new threat. Not all creatures in this strange world are friendly. Swim through the giant Titan Holefish, encounter the haunting Shadow Leviathan, and visit the adorable Pengwings. Something undiscovered lurks around every corner. Cruise through enchanting and perilous biomes in your modular Seatruck. Blast across the snowy tundra on a Snowfox hoverbike. Survive the harsh climate by constructing extensive habitats, scavenging for resources, and crafting equipment. Below Zero presents entirely new environments for you to survive, study, and explore. Maneuver between erupting Thermal Vents to discover ancient alien artifacts. Clamber up snow covered peaks and venture into the icy caves of Glacial Basin. Become mesmerized by the glittering, mammoth crystals of the Crystal Caverns. Swim beneath the blue-lit, arching expanses of Twisty Bridges. With limited resources, you must improvise to survive on your own. What happened to the scientists who lived and worked here? Logs, items, and databanks scattered among the debris paint a new picture of the incident. Abandoned research stations dot the region. Uncover the truthĪlterra left in a hurry after a mysterious incident. Arriving with little more than your wits and some survival equipment, you set out to investigate what happened to your sister. Submerge yourself in an all-new, sub-zero expedition in an arctic region of Planet 4546B. It is a new chapter in the Subnautica universe, and is developed by Unknown Worlds. But before we could do that, we needed the right data-and the right question.Below Zero is an underwater adventure game set on an alien ocean world. We set out to perform a John Henry-esque test: to find out whether some of these no-code-required tools could outperform a code-based approach, or at least deliver results that were accurate enough to make decisions at a lower cost than a data scientist's billable hours. ML vendors tout their products as being an "easy button" for finding relationships in data that may not be obvious, uncovering the correlation between data points and overall outcomes-and pointing people to solutions that traditional business analysis would take humans days, months, or years to uncover through traditional statistical or quantitative analysis. While the work on DALL-E is amazing and will have a significant impact on the manufacture of memes, deep fakes, and other imagery that was once the domain of human artists (using prompts like " in the style of Edvard Munch's The Scream"), easy-to-use machine learning analytics involving the sorts of data that businesses and individuals create and work with every day can be just as disruptive (in the most neutral sense of that word). A growing class of "no-code" and "low-code" machine learning tools are making a number of ML tasks increasingly approachable, taking the powers of machine learning analytics that were once the sole provenance of data scientists and programmers and making them accessible to business analysts and other non-programming end users. "'Data-driven' is a reality for machine learning or data science projects!") But we learned a lot, and the biggest lesson was that machine learning succeeds only when you ask the right questions of the right data with the right tool. ("It turns out 'data-driven' is not just a joke or a buzzword," said Amazon Web Services Senior Product Manager Danny Smith when we checked in with him for some advice. Readers who have been with us for a while, or at least since the summer of 2021, will remember that time we tried to use machine learning to do some analysis-and didn't exactly succeed. Build a model from bad data and you get bad predictions and bad output-just ask the developers of Microsoft's Tay Twitterbot about that.įor a much less spectacular failure, just look to our back pages. What we call "AI" is dependent upon the construction of models from data using statistical approaches developed by flesh-and-blood humans, and it can fail just as spectacularly as it succeeds. (Spoiler alert: It has not.)Īnd as Ars' Matt Ford recently pointed out here, artificial intelligence may be artificial, but it's not "intelligence"-and it certainly isn't magic. And some people even think that an AI has attained sentience. Natural language processing (NLP) systems have grown closer to approximating human writing and text. Specialized algorithms, including OpenAI's DALL-E, have demonstrated the ability to generate images based on text prompts with increasing canniness. Over the past year, machine learning and artificial intelligence technology have made significant strides.
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