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Complete Star Trek® Theme Music – 3rd Edition Piano Solo Piano Solo Songbook

Series: Piano Solo Songbook

• Composer: Various
• Price: $24.99 (US)

Calling all Trekkies! This updated piano solo songbook features the musical themes from the TV shows and movies. Includes: Star Trek – The Motion Picture • Star Trek II: The Wrath of Kahn • Star Trek III: The Search for Spock • Star Trek IV: The Voyage Home • Star Trek V: The Final Frontier • Star Trek VI: The Undiscovered Country • Star Trek: Generations • Star Trek: The Next Generation • Star Trek: Deep Space Nine • Star Trek: Voyager • and more!

• Enterprise Theme (Where My Heart Will Take Me) (from the Paramount T.V. Series STAR TREK: ENTERPRISE)
• Star Trek(R) Insurrection (Theme from the Paramount Motion Picture STAR TREK: INSURRECTION)
• The Moon's A Window To Heaven (from the Paramount Motion Picture STAR TREK V: THE FINAL FRONTIER)
• Theme From “Star Trek(R)” (from the Paramount Television Series STAR TREK)
• Star Trek - Deep Space Nine(R) (Theme from the Paramount Television Series STAR TREK: DEEP SPACE NINE)
• Star Trek(R) First Contact (Theme from the Paramount Motion Picture STAR TREK: FIRST CONTACT)
• Star Trek(R) Generations (Theme from the Paramount Motion Picture STAR TREK: GENERATIONS)
• Star Trek(R) The Motion Picture (Theme from the Paramount Picture STAR TREK: THE MOTION PICTURE)
• Star Trek - The Next Generation(R) (Theme from the Paramount Television Series STAR TREK: THE NEXT GENERATION)
• Star Trek(R) III - The Search For Spock (Theme from the Paramount Motion Picture STAR TREK III: THE SEARCH FOR SPOCK)
• Star Trek(R) VI - The Undiscovered Country (Suite from the Paramount Motion Picture STAR TREK VI: THE UNDISCOVERED COUNTRY)
• Star Trek(R) IV - The Voyage Home (Theme from the Paramount Motion Picture STAR TREK IV: THE VOYAGE HOME)
• Star Trek - Voyager(R) (Theme from the Paramount Television Series STAR TREK: VOYAGER)
• Star Trek(R) II - The Wrath Of Khan (Theme from the Paramount Motion Picture STAR TREK II: THE WRATH OF KHAN)

Download the Digital Sheet Music for Complete Star Trek® Theme Music – 3rd Edition.

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• Piano/Keyboard

Product Details

• Inventory: #HL 00313030
• ISBN: 9780793552467
• UPC: 073999130300
• Width: 9.0"
• Length: 12.0"
• Page Count: 82 Pages

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Star Trek - Into Darkness (Piano Solo Songbook) Paperback – September 1, 2013

Purchase options and add-ons.

• Print length 40 pages
• Language English
• Publisher Hal Leonard
• Publication date September 1, 2013
• Dimensions 9 x 0.1 x 12 inches
• ISBN-10 1480352853
• ISBN-13 978-1480352858
• See all details

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Product details

• Publisher ‏ : ‎ Hal Leonard; Media tie-in edition (September 1, 2013)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 40 pages
• ISBN-10 ‏ : ‎ 1480352853
• ISBN-13 ‏ : ‎ 978-1480352858
• Item Weight ‏ : ‎ 5.4 ounces
• Dimensions ‏ : ‎ 9 x 0.1 x 12 inches
• #1,750 in Musicals & Film Songbooks
• #8,519 in Piano Songbooks
• #139,325 in Humor & Entertainment (Books)

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Star Trek Theme (Pg 20)

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Star Trek's Holodeck recreated using ChatGPT and video game assets

In Star Trek: The Next Generation , Captain Picard and the crew of the U.S.S. Enterprise leverage the holodeck, an empty room capable of generating 3D environments, to prepare for missions and to entertain themselves, simulating everything from lush jungles to the London of Sherlock Holmes. Deeply immersive and fully interactive, holodeck-created environments are infinitely customizable, using nothing but language: the crew has only to ask the computer to generate an environment, and that space appears in the holodeck.

Today, virtual interactive environments are also used to train robots prior to real-world deployment in a process called "Sim2Real." However, virtual interactive environments have been in surprisingly short supply. "Artists manually create these environments," says Yue Yang, a doctoral student in the labs of Mark Yatskar and Chris Callison-Burch, Assistant and Associate Professors in Computer and Information Science (CIS), respectively. "Those artists could spend a week building a single environment," Yang adds, noting all the decisions involved, from the layout of the space to the placement of objects to the colors employed in rendering.

That paucity of virtual environments is a problem if you want to train robots to navigate the real world with all its complexities. Neural networks, the systems powering today's AI revolution, require massive amounts of data, which in this case means simulations of the physical world. "Generative AI systems like ChatGPT are trained on trillions of words, and image generators like Midjourney and DALLE are trained on billions of images," says Callison-Burch. "We only have a fraction of that amount of 3D environments for training so-called 'embodied AI.' If we want to use generative AI techniques to develop robots that can safely navigate in real-world environments, then we will need to create millions or billions of simulated environments."

Enter Holodeck, a system for generating interactive 3D environments co-created by Callison-Burch, Yatskar, Yang and Lingjie Liu, Aravind K. Joshi Assistant Professor in CIS, along with collaborators at Stanford, the University of Washington, and the Allen Institute for Artificial Intelligence (AI2). Named for its Star Trek forebear, Holodeck generates a virtually limitless range of indoor environments, using AI to interpret users' requests. "We can use language to control it," says Yang. "You can easily describe whatever environments you want and train the embodied AI agents."

Holodeck leverages the knowledge embedded in large language models (LLMs), the systems underlying ChatGPT and other chatbots. "Language is a very concise representation of the entire world," says Yang. Indeed, LLMs turn out to have a surprisingly high degree of knowledge about the design of spaces, thanks to the vast amounts of text they ingest during training. In essence, Holodeck works by engaging an LLM in conversation, using a carefully structured series of hidden queries to break down user requests into specific parameters.

Just like Captain Picard might ask Star Trek's Holodeck to simulate a speakeasy, researchers can ask Penn's Holodeck to create "a 1b1b apartment of a researcher who has a cat." The system executes this query by dividing it into multiple steps: first, the floor and walls are created, then the doorway and windows. Next, Holodeck searches Objaverse, a vast library of premade digital objects, for the sort of furnishings you might expect in such a space: a coffee table, a cat tower, and so on. Finally, Holodeck queries a layout module, which the researchers designed to constrain the placement of objects, so that you don't wind up with a toilet extending horizontally from the wall.

To evaluate Holodeck's abilities, in terms of their realism and accuracy, the researchers generated 120 scenes using both Holodeck and ProcTHOR, an earlier tool created by AI2, and asked several hundred Penn Engineering students to indicate their preferred version, not knowing which scenes were created by which tools. For every criterion -- asset selection, layout coherence and overall preference -- the students consistently rated the environments generated by Holodeck more favorably.

The researchers also tested Holodeck's ability to generate scenes that are less typical in robotics research and more difficult to manually create than apartment interiors, like stores, public spaces and offices. Comparing Holodeck's outputs to those of ProcTHOR, which were generated using human-created rules rather than AI-generated text, the researchers found once again that human evaluators preferred the scenes created by Holodeck. That preference held across a wide range of indoor environments, from science labs to art studios, locker rooms to wine cellars.

Finally, the researchers used scenes generated by Holodeck to "fine-tune" an embodied AI agent. "The ultimate test of Holodeck," says Yatskar, "is using it to help robots interact with their environment more safely by preparing them to inhabit places they've never been before."

Across multiple types of virtual spaces, including offices, daycares, gyms and arcades, Holodeck had a pronounced and positive effect on the agent's ability to navigate new spaces.

For instance, whereas the agent successfully found a piano in a music room only about 6% of the time when pre-trained using ProcTHOR (which involved the agent taking about 400 million virtual steps), the agent succeeded over 30% of the time when fine-tuned using 100 music rooms generated by Holodeck.

"This field has been stuck doing research in residential spaces for a long time," says Yang. "But there are so many diverse environments out there -- efficiently generating a lot of environments to train robots has always been a big challenge, but Holodeck provides this functionality."

• Engineering
• Virtual Environment
• Robotics Research
• Civil Engineering
• Artificial Intelligence
• Virtual Reality
• Computer Modeling
• Materials science
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• Search engine
• Mathematical model
• Denaturation (biochemistry)
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Story Source:

Materials provided by University of Pennsylvania School of Engineering and Applied Science . Original written by Ian Scheffler. Note: Content may be edited for style and length.

Journal Reference :

• Yue Yang, Fan-Yun Sun, Luca Weihs, Eli VanderBilt, Alvaro Herrasti, Winson Han, Jiajun Wu, Nick Haber, Ranjay Krishna, Lingjie Liu, Chris Callison-Burch, Mark Yatskar, Aniruddha Kembhavi, Christopher Clark. Holodeck: Language Guided Generation of 3D Embodied AI Environments . Submitted to arXiv , 2024 DOI: 10.48550/arXiv.2312.09067

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The Piano season 2: Release date, cast and latest news

The heartwarming series is back for a second instalment.

• Katelyn Mensah
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The Piano is back!

It was confirmed last year that the heartwarming series would be returning for a second season , and now the release date has officially been confirmed by Channel 4.

The new season will see the return of Claudia Winkleman, Lang Lang and Mika, and will have an epic seven episodes, giving amateur pianists the chance to perform at the Royal Festival Hall.

With the news of the return, here's everything you need to know about The Piano season 2.

The Piano season 2 release date

CONFIRMED: It has been confirmed The Piano season 2 will premiere on Sunday 28th April at 9pm on Channel 4 .

More like this

The series will air across seven weeks on Channel 4, with amateur pianists being invited to play on public pianos at the likes of London St Pancras, Leeds, Glasgow and Birmingham train stations.

What is The Piano about?

The Piano first hit screens in February 2023, which saw cameras placed around pianos in train across the UK, with classical pianist Lang Lang and singer Mika covertly watching to see who will play the instrument.

When the series first aired, Channel 4 teased what viewers could expect: "From nonagenarians who have been playing for 80 years to 12-year-olds who have never played in public before, those who taught themselves to play the classics in lockdown to players who feel the music, composing pieces about their life experiences, and someone with no sight who against all the odds has mastered Chopin, commuters in train stations across the country will be stopped in their tracks as heartfelt, emotional and uplifting performances take place."

The Piano season 2 host

Claudia Winkleman will return as host extraordinaire on The Piano.

Best known for her eccentric looks on The Traitors and hilarious one-liners on Strictly Come Dancing , alongside Tess Daly, Winkleman also hosted the first season of The Piano.

The Piano season 2 judges

Lang Lang and Mika will also be returning alongside Winkleman as judges.

Lang Lang is an award-winning pianist who has played with the Berlin Philharmonic and the Vienna Philharmonic, and has played for former US president Barack Obama and the late Queen Elizabeth II.

Mika is a singer-songwriter who rose to fame in 2007 with his album Life in Cartoon Motion, with his hit song Grace Kelly rising high in the charts.

He has since been a judge and mentor on the French version of The Voice and Italy's X Factor, and in 2022, he co-hosted the Eurovision Song Contest.

Is there a trailer for The Piano season 2?

Not yet . Channel 4 is yet to release a trailer for The Piano, but we'll be sure to update this page once it has!

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The Piano season 2 premieres on Sunday 28th April at 9pm on Channel 4.

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‘Star Trek: Strange New Worlds’ Renewed for Season 4; ‘Lower Decks’ to Conclude With Season 5 (EXCLUSIVE)

By Adam B. Vary

Adam B. Vary

Senior Entertainment Writer

• ‘Abigail’ Filmmakers Radio Silence on Their Genre-Hopping Vampire Thriller and Honoring Angus Cloud’s Final Performance  13 hours ago
• Marvel Lays Off 15 Staffers 2 days ago
• ‘Star Trek: Strange New Worlds’ Renewed for Season 4; ‘Lower Decks’ to Conclude With Season 5 (EXCLUSIVE) 5 days ago

“ Star Trek : Strange New Worlds,” currently in production on its third season, has been renewed by Paramount+ for Season 4. Meanwhile, “ Star Trek: Lower Decks ,” the first animated “Star Trek” comedy, will conclude its run on the streamer with its fifth season, which will debut in the fall.

Popular on Variety

“Lower Decks” charted brand new territory for “Star Trek” when it debuted in 2020, as both an animated comedy and a series that focused on the junior officers of the USS Cerritos: Beckett Mariner (Tawny Newsome), Brad Boimler (Jack Quaid), D’Vana Tendi (Noël Wells) and Sam Rutherford (Eugene Cordero). Set in the years following the feature film “Star Trek: Nemesis,” the series has included voice cameos from many beloved “Star Trek” alumni, like George Takei, Jonathan Frakes, Marina Sirtis, John de Lancie, Will Wheaton, Armin Shimerman, Nana Visitor and Robert Duncan McNeill.

Given its premise, concluding “Lower Decks” make sense considering the main four characters all received promotions in Season 4. But in a message to fans, Kurtzman and executive producer and showrunner Mike McMahan left the turbolift doors open for continuing the characters’ stories following their time at the bottom of the Starfleet pecking order. 

The “Star Trek” TV universe, overseen by Kurtzman through his Secret Hideout production company and produced by CBS Studios, has enjoyed a robust expansion since “Star Trek: Discovery” first premiered in 2017. Along with “Strange New Worlds,” the made-for-television movie “Star Trek: Section 31” recently concluded production with star Michelle Yeoh, and the new series “Star Trek: Starfleet Academy” will begin shooting later this year.

“It has been incredibly rewarding to continue to build the Star Trek universe, and we’re so grateful to Secret Hideout and our immensely talented casts and producers,” said Jeff Grossman, executive vice president of Programming at Paramount+. “‘Strange New Worlds’ has found the perfect blend of action, adventure and humor. Similarly, ‘Star Trek: Lower Decks’ has brought the laughs with an ample amount of heart to the franchise across its four seasons. We can’t wait for audiences to see what is in store for the crew of the U.S.S. Cerritos in this final season.”

“‘Lower Decks’ and ‘Strange New Worlds’ are integral to the ‘Star Trek’ franchise, expanding the boundaries of the universe and exploring new and exciting worlds,” said CBS Studios president David Stapf. “We are extraordinarily proud of both series as they honor the legacy of what Gene Roddenberry created almost 60 years ago. We are so grateful to work with Secret Hideout, Alex Kurtzman, Mike McMahan, Akiva Goldsman, Henry Alonso Myers and the cast, crews and artists who craft these important and entertaining stories for fans around the world.”

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Engineers recreate Star Trek's Holodeck using ChatGPT and video game assets

by Ian Scheffler, University of Pennsylvania

In "Star Trek: The Next Generation," Captain Picard and the crew of the U.S.S. Enterprise leverage the Holodeck, an empty room capable of generating 3D environments, of preparing for missions and entertaining them, simulating everything from lush jungles to the London of Sherlock Holmes.

Deeply immersive and fully interactive, Holodeck-created environments are infinitely customizable, using nothing but language; the crew has only to ask the computer to generate an environment, and that space appears in the Holodeck.

Today, virtual interactive environments are also used to train robots prior to real-world deployment in a process called "Sim2Real." However, virtual interactive environments have been in surprisingly short supply.

"Artists manually create these environments," says Yue Yang, a doctoral student in the labs of Mark Yatskar and Chris Callison-Burch, Assistant and Associate Professors in Computer and Information Science (CIS), respectively. "Those artists could spend a week building a single environment," Yang adds, noting all the decisions involved, from the layout of the space to the placement of objects to the colors employed in rendering.

That paucity of virtual environments is a problem if you want to train robots to navigate the real world with all its complexities. Neural networks, the systems powering today's AI revolution, require massive amounts of data, which in this case means simulations of the physical world.

"Generative AI systems like ChatGPT are trained on trillions of words, and image generators like Midjourney and DALL-E are trained on billions of images," says Callison-Burch. "We only have a fraction of that amount of 3D environments for training so-called 'embodied AI.' If we want to use generative AI techniques to develop robots that can safely navigate in real-world environments, then we will need to create millions or billions of simulated environments."

Enter Holodeck , a system for generating interactive 3D environments co-created by Callison-Burch, Yatskar, Yang and Lingjie Liu, Aravind K. Joshi Assistant Professor in CIS, along with collaborators at Stanford, the University of Washington, and the Allen Institute for Artificial Intelligence (AI2). Named for its Star Trek forebear, Holodeck generates a virtually limitless range of indoor environments, using AI to interpret users' requests.

The paper is published on the arXiv preprint server.

"We can use language to control it," says Yang. "You can easily describe whatever environments you want and train the embodied AI agents."

Holodeck leverages the knowledge embedded in large language models (LLMs), the systems underlying ChatGPT, and other chatbots. "Language is a very concise representation of the entire world," says Yang. Indeed, LLMs turn out to have a surprisingly high degree of knowledge about the design of spaces, thanks to the vast amounts of text they ingest during training. In essence, Holodeck works by engaging an LLM in conversation, using a carefully structured series of hidden queries to break down user requests into specific parameters.

Just like Captain Picard might ask Star Trek's Holodeck to simulate a speakeasy, researchers can ask Penn's Holodeck to create "a 1b1b apartment of a researcher who has a cat." The system executes this query by dividing it into multiple steps: First, the floor and walls are created, then the doorway and windows.

Next, Holodeck searches Objaverse , a vast library of premade digital objects, for the sort of furnishings you might expect in such a space: a coffee table, a cat tower, and so on. Finally, Holodeck queries a layout module, which the researchers designed to constrain the placement of objects so that you don't wind up with a toilet extending horizontally from the wall.

To evaluate Holodeck's abilities, in terms of their realism and accuracy, the researchers generated 120 scenes using both Holodeck and ProcTHOR, an earlier tool created by AI2, and asked several hundred Penn Engineering students to indicate their preferred version, not knowing which scenes were created by which tools. For every criterion—asset selection, layout coherence, and overall preference—the students consistently rated the environments generated by Holodeck more favorably.

The researchers also tested Holodeck's ability to generate scenes that are less typical in robotics research and more difficult to manually create than apartment interiors, like stores, public spaces, and offices. Comparing Holodeck's outputs to those of ProcTHOR, which were generated using human-created rules rather than AI-generated text, the researchers found once again that human evaluators preferred the scenes created by Holodeck. That preference held across a wide range of indoor environments, from science labs to art studios, locker rooms to wine cellars.

Finally, the researchers used scenes generated by Holodeck to "fine-tune" an embodied AI agent. "The ultimate test of Holodeck," says Yatskar, "is using it to help robots interact with their environment more safely by preparing them to inhabit places they've never been before."

Across multiple types of virtual spaces, including offices, daycares, gyms and arcades, Holodeck had a pronounced and positive effect on the agent's ability to navigate new spaces.

For instance, whereas the agent successfully found a piano in a music room only about 6% of the time when pre-trained using ProcTHOR (which involved the agent taking about 400 million virtual steps), the agent succeeded over 30% of the time when fine-tuned using 100 music rooms generated by Holodeck.

"This field has been stuck doing research in residential spaces for a long time," says Yang. "But there are so many diverse environments out there—efficiently generating a lot of environments to train robots has always been a big challenge, but Holodeck provides this functionality."

In June, the researchers will present Holodeck at the 2024 Institute of Electrical and Electronics Engineers (IEEE) and Computer Vision Foundation (CVF) Computer Vision and Pattern Recognition (CVPR) Conference in Seattle, Washington.

GitHub: yueyang1996.github.io/holodeck/

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Penn Engineers Recreate Star Trek’s Holodeck Using ChatGPT and Video Game Assets

By Ian Scheffler

In Star Trek: The Next Generation , Captain Picard and the crew of the U.S.S. Enterprise leverage the holodeck, an empty room capable of generating 3D environments, to prepare for missions and to entertain themselves, simulating everything from lush jungles to the London of Sherlock Holmes . Deeply immersive and fully interactive, holodeck-created environments are infinitely customizable, using nothing but language: the crew has only to ask the computer to generate an environment, and that space appears in the holodeck.

Today, virtual interactive environments are also used to train robots prior to real-world deployment in a process called “Sim2Real.” However, virtual interactive environments have been in surprisingly short supply. “Artists manually create these environments,” says Yue Yang , a doctoral student in the labs of Mark Yatskar and Chris Callison-Burch , Assistant and Associate Professors in Computer and Information Science (CIS), respectively. “Those artists could spend a week building a single environment,” Yang adds, noting all the decisions involved, from the layout of the space to the placement of objects to the colors employed in rendering.

That paucity of virtual environments is a problem if you want to train robots to navigate the real world with all its complexities. Neural networks, the systems powering today’s AI revolution, require massive amounts of data, which in this case means simulations of the physical world. “Generative AI systems like ChatGPT are trained on trillions of words, and image generators like Midjourney and DALLE  are trained on billions of images,” says Callison-Burch. “We only have a fraction of that amount of 3D environments for training so-called ‘embodied AI.’ If we want to use generative AI techniques to develop robots that can safely navigate in real-world environments, then we will need to create millions or billions of simulated environments.” 

If we want to use generative AI techniques to develop robots that can safely navigate in real-world environments, then we will need to create millions or billions of simulated environments. Chris Callison-Burch, Associate Professor Computer and Information Science (CIS)

Enter Holodeck , a system for generating interactive 3D environments co-created by Callison-Burch, Yatskar, Yang and Lingjie Liu , Aravind K. Joshi Assistant Professor in CIS, along with collaborators at Stanford, the University of Washington, and the Allen Institute for Artificial Intelligence (AI2). Named for its Star Trek forebear, Holodeck generates a virtually limitless range of indoor environments, using AI to interpret users’ requests. “We can use language to control it,” says Yang. “You can easily describe whatever environments you want and train the embodied AI agents.”

Holodeck leverages the knowledge embedded in large language models (LLMs), the systems underlying ChatGPT and other chatbots. “Language is a very concise representation of the entire world,” says Yang. Indeed, LLMs turn out to have a surprisingly high degree of knowledge about the design of spaces, thanks to the vast amounts of text they ingest during training. In essence, Holodeck works by engaging an LLM in conversation, using a carefully structured series of hidden queries to break down user requests into specific parameters. 

Just like Captain Picard might ask Star Trek’s Holodeck to simulate a speakeasy, researchers can ask Penn’s Holodeck to create “a 1b1b apartment of a researcher who has a cat.” The system executes this query by dividing it into multiple steps: first, the floor and walls are created, then the doorway and windows. Next, Holodeck searches Objaverse , a vast library of premade digital objects, for the sort of furnishings you might expect in such a space: a coffee table, a cat tower, and so on. Finally, Holodeck queries a layout module, which the researchers designed to constrain the placement of objects, so that you don’t wind up with a toilet extending horizontally from the wall. 

To evaluate Holodeck’s abilities, in terms of their realism and accuracy, the researchers generated 120 scenes using both Holodeck and ProcTHOR, an earlier tool created by AI2, and asked several hundred Penn Engineering students to indicate their preferred version, not knowing which scenes were created by which tools. For every criterion — asset selection, layout coherence and overall preference — the students consistently rated the environments generated by Holodeck more favorably. 

The researchers also tested Holodeck’s ability to generate scenes that are less typical in robotics research and more difficult to manually create than apartment interiors, like stores, public spaces and offices. Comparing Holodeck’s outputs to those of ProcTHOR, which were generated using human-created rules rather than AI-generated text, the researchers found once again that human evaluators preferred the scenes created by Holodeck. That preference held across a wide range of indoor environments, from science labs to art studios, locker rooms to wine cellars. 

Finally, the researchers used scenes generated by Holodeck to “fine-tune” an embodied AI agent. “The ultimate test of Holodeck,” says Yatskar, “is using it to help robots interact with their environment more safely by preparing them to inhabit places they’ve never been before.”

Across multiple types of virtual spaces, including offices, daycares, gyms and arcades, Holodeck had a pronounced and positive effect on the agent’s ability to navigate new spaces. 

For instance, whereas the agent successfully found a piano in a music room only about 6% of the time when pre-trained using ProcTHOR (which involved the agent taking about 400 million virtual steps), the agent succeeded over 30% of the time when fine-tuned using 100 music rooms generated by Holodeck. 

“This field has been stuck doing research in residential spaces for a long time,” says Yang. “But there are so many diverse environments out there — efficiently generating a lot of environments to train robots has always been a big challenge, but Holodeck provides this functionality.” 

In June, the researchers will present Holodeck at the 2024 Institute of Electrical and Electronics Engineers (IEEE) and Computer Vision Foundation (CVF) Computer Vision and Pattern Recognition (CVPR) Conference in Seattle, Washington.

This study was conducted at the University of Pennsylvania School of Engineering and Applied Science and at the Allen Institute for Artificial Intelligence (AI2). 

Additional co-authors include Fan-Yun Sun, Jiajun Wu, and Nick Haber at Stanford; Ranjay Krishna at the University of Washington; Luca Weihs, Eli Vanderbilt, Alvaro Herrasti, Winson Han, Aniruddha Kembhavi, and Christopher Clark at AI2.