Robots are inching closer to being helpers in our homes. Remember Rosie from "The Jetsons?" For those too young, Rosie was a futuristic robot helper in a classic cartoon. Now, the idea of having such a robot in our homes feels like it's inching closer to reality with the unveiling of NEO Gamma. Developed by the artificial intelligence company 1X, this isn't your clunky, metallic automaton.

Recent advances in robot learning have shown promise in enabling robots to perform a variety of manipulation tasks and generalize to novel scenarios. One of the key contributing factors to this progress is the scale of robot data used to train the models. To obtain large-scale datasets, prior approaches have relied on either demonstrations requiring high human involvement or engineering-heavy autonomous data collection schemes, both of which are challenging to scale. To mitigate this issue, we propose an alternative route and leverage text-to-image foundation models widely used in computer vision and natural language processing to obtain meaningful data for robot learning without requiring additional robot data. We term our method Robot Learning with Semantically Imagened Experience (ROSIE). Specifically, we make use of the state of the art text-to-image diffusion models and perform aggressive data augmentation on top of our existing robotic manipulation datasets via inpainting various unseen objects for manipulation, backgrounds, and distractors with text guidance. Through extensive real-world experiments, we show that manipulation policies trained on data augmented this way are able to solve completely unseen tasks with new objects and can behave more robustly w.r.t. novel distractors. In addition, we find that we can improve the robustness and generalization of high-level robot learning tasks such as success detection through training with the diffusion-based data augmentation. The project's website and videos can be found at diffusion-rosie.github.io

"She cooks, she cleans, and she still finds time to play ball with Elroy," George and Jane Jetsons' six-and-a-half-year-old son. Set in the year 2062 and described in the 1960s animated sitcom The Jetsons as an "aluminum-encased, battery-powered robotic maid" who is the "perfect answer for any modern family," Rosie the Robot takes care of chores around the house while also serving as friend and confidante of mother Jane. Sarcastic and funny, Rosie is a hardworking nanny and aunt figure to children Elroy and Judy. While many technologies The Jetsons predicted for 2062 have become reality, such as video calls and smart watches, the full realization of robots as the 1960s ideal friend and helper who makes life easier has yet to be fulfilled. For twenty-five years, roboticist Daniel Theobald has been on a mission to create robots that can solve the world's most pressing problems.

We propose a computational model of situated language comprehension based on the Indexical Hypothesis that generates meaning representations by translating amodal linguistic symbols to modal representations of beliefs, knowledge, and experience external to the linguistic system. This Indexical Model incorporates multiple information sources, including perceptions, domain knowledge, and short-term and long-term experiences during comprehension. We show that exploiting diverse information sources can alleviate ambiguities that arise from contextual use of underspecific referring expressions and unexpressed argument alternations of verbs. The model is being used to support linguistic interactions in Rosie, an agent implemented in Soar that learns from instruction.

Language models are increasingly attracting interest from writers. However, such models lack long-range semantic coherence, limiting their usefulness for longform creative writing. We address this limitation by applying language models hierarchically, in a system we call Dramatron. By building structural context via prompt chaining, Dramatron can generate coherent scripts and screenplays complete with title, characters, story beats, location descriptions, and dialogue. We illustrate Dramatron's usefulness as an interactive co-creative system with a user study of 15 theatre and film industry professionals. Participants co-wrote theatre scripts and screenplays with Dramatron and engaged in open-ended interviews. We report critical reflections both from our interviewees and from independent reviewers who watched stagings of the works to illustrate how both Dramatron and hierarchical text generation could be useful for human-machine co-creativity. Finally, we discuss the suitability of Dramatron for co-creativity, ethical considerations -- including plagiarism and bias -- and participatory models for the design and deployment of such tools.

Artificial something that is not natural, or, anything that is human-made. AI is a broad area of computer science that makes machines seem like they have human intelligence. It's the broader category -- all Machine Learning and Deep Learning systems count as Artificial Intelligence. The vice versa is not valid, tho. Not all AI is Machine Learning or Deep Learning.

Facebook recently showed off the progress its AI research team has made in the realm of household robotics. The dream is to take the virtual assistant out of the speaker and put it into an autonomous body capable of traversing your house. To accomplish a task like checking to see whether you locked the front door or retrieving a cell phone that's ringing in an upstairs bedroom, AI assistants of the future must learn to plan their route, navigate effectively, look around their physical environment, listen to what's happening around them, and build memories of the 3D space. Facebook's created a new system called SoundSpaces that gives robots the ability to interpret sounds. Current virtual assistants merely listen for wake words and then use natural language processing to interpret verbal commands as triggers. While the microphone array technology behind some of these assistants is impressive, they're merely designed to pick up voices in noisy environments.

There's literally a lot more stuff in space than there was last week – or at least, the number of active human-made satellites in Earth's orbit has gone up quite a bit, thanks to the launch of SpaceX's first 60 production Starlink satellites. This week also saw movement in other key areas of commercial space, and some continued activity in early-stage space startup ecosystem encouragement. Some of the'New Space' companies are flexing the advantages that are helping them shake up an industry typically reserved for just a few deep-pocketed defence contractors, and NASA is getting ready for planetary space exploration in more ways than one. The 60 Starlink satellites that SpaceX launched this week are the first that aren't specifically designated as tester vehicles, even though it launched a batch of 60 earlier this year, too. These ones will form the cornerstone of between 300-400 or so that will provide the first commercial service to customers in the U.S. and Canada next year, if everything goes to SpaceX's plan for its new global broadband service.

Welcome to TechTalks' AI book reviews, a series of posts that explore the latest literature on AI. The media is rife with stories that warn of AI algorithms bringing people back from the dead, AI algorithms developing secret languages, mass technological unemployment, and a looming robot apocalypse. Movies and TV series like Her, The Circleand Westworld,which present a mystic portrayal of conscious machines and human-level AI being just around the corner. Rebooting AI is a refreshing read and a much-needed reality check on the current confusing state of artificial intelligence. Consider the following text, mentioned in Rebooting AI: "Elsie tried to reach her aunt on the phone, but she didn't answer." You don't need to be a genius to quickly make the following assumptions after reading this sentence: But even the most sophisticated AI algorithm would struggle to draw the same conclusions.

Welcome to TechTalks' AI book reviews, a series of posts that explore the latest literature on AI. The media is rife with stories that warn of AI algorithms bringing people back from the dead, AI algorithms developing secret languages, mass technological unemployment, and a looming robot apocalypse. Movies and TV series like Her, The Circle and Westworld, which present a mystic portrayal of conscious machines and human-level AI being just around the corner. Rebooting AI is a refreshing read and a much-needed reality check on the current confusing state of artificial intelligence. Consider the following text, mentioned in Rebooting AI: "Elsie tried to reach her aunt on the phone, but she didn't answer." You don't need to be a genius to quickly make the following assumptions after reading this sentence: But even the most sophisticated AI algorithm would struggle to draw the same conclusions.