Lastly, I was really excited to check out Nightdive’s interpretation of Cyberspace, but the first terminal I found didn’t seem to be operable in this demo. The gun came with one type of ammo, but I only ever picked up a different type that I couldn’t seem to swap out for. I also couldn’t figure out for the life of me how to switch my pistol’s ammo out. The demo doesn’t allow you to save, so after I died early on in my first run, I had to start from the beginning. At first, I had some camera wackiness as I passed through doorways or went from room to room, but the longer I played, the more unstable my camera movement became. It took me about an hour to complete the demo. ![]() I wasn’t afraid of her because I knew her. Slowly, I regained my footing, and as I approached the end of the demo, I could feel my confidence coming back. I felt lost, scrambling for traction, all the while I knew SHODAN could see my every move, my every dead end. For a while I stood there, watching these tubes breathe in and out, and I felt even more insecure and vulnerable than I had in the original. Various tubes and panels almost seemed to be breathing, as if SHODAN herself was embodied in the station, and I was navigating her interior. Gemini is also excellent at inflating Google's PR language-if the models were any less capable and revolutionary, would the marketing copy be any less breathless? It's doubtful.SHODAN’s presence felt somehow even more pervasive as I walked along corridor after corridor. Google trained a special coding-centric version of Gemni called AlphaCode 2, which "excels at solving competitive programming problems that go beyond coding to involve complex math and theoretical computer science," according to Google. "On TPUs," Google says, "Gemini runs significantly faster than earlier, smaller and less-capable models."Īnd it's purportedly great at coding. Google also claims that Gemini is more scalable and efficient than its previous AI models when run on Google's custom Tensor Processing Units (TPU). From our informal testing so far, Gemini Pro appears to perform much better than the previous version of Bard, which was based on Google's PaLM 2 language model. As mentioned above, Google Bard now runs a specially tuned version of Gemini Pro. I’m genuinely excited for what’s ahead and for the opportunities Gemini will unlock for people everywhere."Īlthough Gemini will come in three sizes, only the mid-level model is available for public use. "This new era of models represents one of the biggest science and engineering efforts we’ve undertaken as a company. ![]() "These are the first models of the Gemini era and the first realization of the vision we had when we formed Google DeepMind earlier this year," wrote Google CEO Sundar Pichai in a statement. Google Gemini promotional video from Google. That means Nano, the smallest, is designed to run locally on consumer devices, while Ultra can only run on data center hardware. ![]() More parameters means a bigger neural network that is generally more capable of executing more complex tasks but requires more computational power to run. Each is likely separated in complexity by parameter count. Google says Gemini will be available in three sizes: Gemini Ultra ("for highly complex tasks"), Gemini Pro ("for scaling across a wide range of tasks"), and Gemini Nano ("for on device tasks" like Google's Pixel 8 Pro smartphone). "Its remarkable ability to extract insights from hundreds of thousands of documents through reading, filtering, and understanding information will help deliver new breakthroughs at digital speeds in many fields from science to finance." "Gemini 1.0’s sophisticated multimodal reasoning capabilities can help make sense of complex written and visual information," writes Google. Google says this will power a new era in computing, and it hopes to tightly integrate the technology into its products. The goal is to make a type of artificial intelligence that can accurately solve problems, give advice, and answer questions in various fields-from the mundane to the scientific. That means it can process text, code, images, and even audio. Like GPT-4, Gemini can handle multiple types (or "modes") of input, making it multimodal. Further Reading The AI race heats up: Google announces PaLM 2, its answer to GPT-4
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