Hitachi has developed a metaverse-based system that lets skilled workers run remote demonstrations using real-world factory equipment. This system is designed to help industries where know-how is concentrated among aging veterans.
The system uses a virtual reality headset to superimpose an image of the instructor’s hands on a drum-shaped machine. The instructor, who is in another location, can move freely within the metaverse factory and can also see the entire work site from above.
The system combines ceiling camera and sensor data to re-create the factory in the metaverse in real time. Instructors can monitor the trainee’s movements through the virtual link and offer guidance.
Hitachi deployed proprietary data analysis technology for efficient processing of 3D data. This enables the metaverse to operate without lag on conventional Wi-Fi connections, as well as on 5G networks. The platform is compatible with off-the-shelf cameras and virtual reality devices.
In the future, Hitachi looks to field-test the metaverse at railroad construction sites and power plants. The company is also considering taking it outside the group.
The metaverse-based system has the potential to revolutionize the way that training is conducted in the manufacturing sector. Veteran employees can now train younger workers remotely, from home or an office. This is especially important in Japan, where the population is aging rapidly and there is a serious labor shortage.
The metaverse-based system is also being used in other industries, such as automotive manufacturing. BMW has developed a virtual factory to test production lines for optimum output before building them in the real world.
The metaverse has the potential to revolutionize the way that we work and learn. By providing a virtual space where people can interact with each other and with real-world objects, the metaverse can help us to bridge distances and collaborate more effectively.
Right in time for Halloween 2024, Meta has launched Meta Spirit LM, its first open-source multimodal language model capable of handling both text and speech inputs and outputs. This groundbreaking model directly challenges similar AI technologies such as OpenAI’s GPT-4 and Hume’s EVI 2, along with specific text-to-speech (TTS) and speech-to-text (ASR) tools like ElevenLabs.
The Future of AI Agents
Created by Meta’s Fundamental AI Research (FAIR) team, Spirit LM open source seeks to enhance AI voice systems by offering more natural and expressive speech generation. It also tackles multimodal tasks, including automatic speech recognition (ASR), text-to-speech (TTS), and speech classification.
However, for the time being, Spirit LM open source is only available for non-commercial use under Meta’s FAIR Noncommercial Research License. This allows researchers to modify and experiment with the model, but any commercial usage or redistribution of the models must adhere to the noncommercial stipulations.
A New Approach to Speech and Text AI
Most traditional AI voice models first convert spoken words into text using ASR, then process that text through a language model and finally use TTS to produce the spoken output. While this approach works, it often fails to capture the full emotional and tonal range of natural human speech.
Meta Spirit LM open source solves this issue by integrating phonetic, pitch, and tone tokens, allowing it to create more expressive and emotionally nuanced speech. The model is available in two variants:
Spirit LM Base: Focuses on phonetic tokens for speech generation and processing.
Spirit LM Expressive: Incorporates pitch and tone tokens to convey emotional cues such as excitement or sadness, bringing an added layer of expressiveness to speech. Both models are trained on datasets that include both speech and text, allowing Spirit LM open source to excel in cross-modal tasks like converting text to speech and vice versa, all while maintaining the natural nuances of speech.
Fully Open-Source for Noncommercial Use
Consistent with Meta’s dedication to open research, Meta Spirit LM open source has been released for non-commercial research purposes. Developers and researchers have full access to the model weights, code, and accompanying documentation to advance their own projects and experiment with new applications.
Mark Zuckerberg, Meta’s CEO, has emphasized the importance of open-source AI, expressing that AI holds the potential to significantly enhance human productivity and creativity, and drive forward innovations in fields like medicine and science.
Potential Applications of Spirit LM Open Source
Meta Spirit LM open source is designed to handle a wide range of multimodal tasks, such as:
Automatic Speech Recognition (ASR): Converting spoken words into written text. Text-to-Speech (TTS): Transforming written text into spoken words. Speech Classification: Recognizing and categorizing speech based on content or emotional tone.
The Spirit LM Expressive model takes things further by not only recognizing emotions in speech but also generating responses that reflect emotional states like joy, surprise, or anger. This opens doors for more lifelike and engaging AI interactions in areas like virtual assistants and customer service systems.
Meta’s Larger AI Research Vision
Meta Spirit LM open source is part of a larger set of open tools and models that Meta FAIR has released. This includes advancements like Segment Anything Model (SAM) 2.1 for image and video segmentation, widely used across industries like medical imaging and meteorology, as well as research aimed at improving the efficiency of large language models.
Meta’s broader mission is to advance Advanced Machine Intelligence (AMI) while ensuring that AI tools are accessible to a global audience. For over a decade, the FAIR team has been leading research that aims to benefit not just the tech world but society at large.
What Lies Ahead for Meta Spirit LM Open Source?
With Meta Spirit LM open source, Meta is pushing the boundaries of what AI can achieve in integrating speech and text. By making the model open-source and focusing on a more human-like, expressive interaction, Meta is giving the research community the opportunity to explore new ways AI can bridge the gap between humans and machines.
Whether in ASR, TTS, or other AI-driven systems, Spirit LM open source represents a significant leap forward, shaping a future where AI-powered conversations and interactions feel more natural and engaging than ever before.
The U.S. Space Force has awarded SpaceX a contract worth $733 million for eight launches, reinforcing the organization’s efforts to increase competition among space launch providers. This deal is part of the ongoing “National Security Space Launch Phase 3 Lane 1” program, overseen by Space Systems Command (SSC), which focuses on less complex missions involving near-Earth orbits.
Under the contract, SpaceX will handle seven launches for the Space Development Agency and one for the National Reconnaissance Office, all using Falcon 9 rockets. These missions are expected to take place no earlier than 2026.
Space Force launch contract
In 2023, the Space Force divided Phase 3 contracts into two categories: Lane 1 for less risky missions and Lane 2 for heavier payloads and more challenging orbits. Although SpaceX was chosen for Lane 1 launches, competitors like United Launch Alliance and Blue Origin were also in the running. The Space Force aims to foster more competition by allowing new companies to bid for future Lane 1 opportunities, with the next bidding round set for 2024. The overall Lane 1 contract is estimated to be worth $5.6 billion over five years.
Lt. Col. Douglas Downs, SSC’s leader for space launch procurement, emphasized the Space Force’s expectation of more competitors and greater variety in launch providers moving forward. The Phase 3 Lane 1 contracts cover fiscal years 2025 to 2029, with the option to extend for five more years, and the Space Force plans to award at least 30 missions over this period.
While SpaceX has a strong position now, emerging launch providers and new technologies could intensify the competition in the near future.
