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Google Maps Helps Users Cut Down Tailpipe Pollution by Promoting Eco-Friendly Routes

Google Maps

Google Maps’ initiative to promote eco-friendly driving routes is proving successful, with users heeding its advice to reduce greenhouse gas emissions during their trips. The feature, introduced in late 2021, enables users to view the most fuel-efficient routes on Google Maps. In the latest environmental report released by Google, it is estimated that this feature has prevented approximately 1.2 million metric tons of planet-heating carbon dioxide emissions. To put this in perspective, it’s equivalent to taking 250,000 gas-guzzling cars off the road for a whole year.

Initially launched in the US, the fuel-efficient route feature is now available in Canada, Egypt, and almost 40 European countries. Utilizing a machine learning model, Google predicts the most fuel or energy-efficient routes and recommends them to Maps users. If the most fuel-efficient route also happens to be the fastest, Google Maps will automatically default to that option.

To provide more accurate predictions, users can input their car’s engine type, whether it’s gas, diesel, hybrid, or electric. However, it’s worth noting that taking public transit, cycling, or walking still remains more sustainable alternatives, and Google is actively working to enhance Maps usability beyond driving. Efforts to make Maps more immersive have included introducing the “Live View” augmented reality feature in major cities and implementing filters to assist electric vehicle drivers in locating fast chargers.

Google’s analysis reveals that many drivers are indeed choosing less polluting routes for their journeys. By comparing the fuel consumption of Maps users on the recommended eco-friendly routes to what they would have consumed on the fastest route without the tool, Google calculated the tailpipe emissions that were prevented. The total savings amounted to 1.2 million metric tons of avoided CO2 emissions from October 2021, when the feature was launched, until December 2022.

This initiative is part of Google’s broader goal to empower one billion users to make more sustainable choices through its products by 2022. Additionally, Google’s environmental report highlights energy savings achieved through Nest, its smart thermostat product. Over the years, Nest thermostats have saved more than 113 billion kWh of energy and 36 million metric tons of CO2 emissions between 2011 and 2022. In 2022 alone, Nest thermostats helped users conserve more energy than Google consumed that year.

However, Google’s significant carbon footprint is a concern, with emissions surpassing 10.18 million metric tons of CO2 in 2022 alone, comparable to pollution from over 25 gas-fired power plants in a year. Although Google has made progress by reducing its emissions from around 13.6 million metric tons in 2018, it still has a long way to go to achieve its goal of halving emissions by 2030. The company acknowledges the challenges ahead and remains committed to continuing its efforts to minimize its environmental impact.

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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.

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