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PLUS: Archetype AIās New āNewtonā AI Model Learns Physics, Meta Unveils āMeta Spirit LMā
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In todayās AI Report:
šØArchetype AIās New āNewtonā AI Model Learns Physics
šFatal Crash With Teslaās Self-Driving Software
š»Meta Unveils āMeta Spirit LMā
š Trending Tools
š°Funding Frontlines
š¼Whoās Hiring?
Read Time: 3 minutes
šRECENT NEWS
ARCHETYPE AI
šØArchetype AIās New āNewtonā AI Model Learns Physics
Image Source: Archetype AI/āNewton: Zero-Shot Forecasting of a Spring-Mass Systemā/YouTube/Screenshot
Archetype AI, a Physical AI company helping humanity make sense of the world, unveiled a new AI model called āNewtonā that predicts how physical objects move in the physical world.
Key Details:
Physical AI focuses on pioneering AI applications to understand and interact with the physical world.
The physical world often feels complex and chaotic, yet humans have learned to discover the underlying laws that govern it.
For example, Newtonās Laws of Motion explain the relationships between physical objects and the forces acting upon them.
So, what if AI could uncover the underlying laws that govern the physical world without human guidance?
āNewtonā learns complex physics principles from Sensor Data without pre-programmed knowledge.
Sensor Data is information collected by a sensor. For example, a microphone collects sound information.
Why Itās Important:
āNewtonā marks a paradigm shift in AIās interactions with the physical world because it learns from Sensor Data without relying on pre-programmed knowledge.
It can forecast citywide power consumption by analyzing building data (e.g., size, shape, and insulation) and tracking Sensor Data (e.g., wind, humidity, and temperature).
šØWatch āNewtonā predict the behavior of a Spring-Mass System here.
TESLA
šFatal Crash With Teslaās Self-Driving Software
Image Source: Canvaās AI Image Generators/Magic Media
A Tesla relying on Full Self-Driving (FSD) crashed after entering an area of reduced roadway visibility from āconditions such as sun glare or airborne dust.ā
Key Details:
All Teslas with FSD software in America are officially under investigation by the National Highway Traffic Safety Administration (NHTSA) after a fatal crash raised doubts about FSDās handling of ālow-visibility situations.ā
FSD is an advanced driving assistant that helps provide active guidance for the burdensome parts of piloting cars (e.g., braking, steering, or accelerating).
Itās powered by large volumes of Neural Networks (NNs) trained on driving datasets. NNs are an AI framework designed to mimic the human brain.
Tesla Vision uses a network of cameras, NNs, and Computer Vision to self-park, auto-lane change, and navigate traffic. Computer Vision enables computers to interpret, analyze, and extract visual data. It aims to replace Ultrasonic Sensors, LiDAR, and RADAR.
Tesla CEO Elon Musk asserts that humans ādrive with their eyes,ā so autonomous vehicles only need vision.
Why Itās Important:
Waymo uses Ultrasonic sensors, LiDAR, and RADAR in their self-driving Jaguar I-PACE to operate safely in low-visibility settings.
Tesla engineers have tried to convince Musk that LiDAR isnāt a ācrutch.ā However, he believes any company that relies on LiDAR for autonomous capabilities is ādoomed.ā
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AI RESEARCH
š»Meta Unveils āMeta Spirit LMā
Image Source: Metaās AI Team/āSPIRIT-LM: Interleaved Spoken and Written Language Modelā/Screenshot
Meta unveiled āMeta Spirit LM,ā an open-source multimodal AI model that seamlessly integrates text and speech inputs and outputs. In other words, it can process both text and speech inputs and generate both text and speech outputs.
A multimodal AI model can process and generate multiple data types, such as text, images, audio, video, and code.
One of the primary challenges in developing Text-to-Speech (TTS) applications is the ārobot-likeā voice. Traditionally, building TTS applications involves a multi-step process. First, Automatic Speech Recognition (ASR) convert spoken words into text. Then, an AI model processes this text. Finally, the processed text is converted back into spoken words.
However, this approach often leads to a loss in expressive quality. For example, nuances such as tone, emotion, and pitch are stripped away. āMeta Spirit LMā solves this issue by allowing an AI model to cross modalities more seamlessly.
By seamlessly integrating both text and speech inputs and outputs, āMeta Spirit LMā can learn to capture and replicate the nuances of spoken words. This breakthrough reduces the ārobot-likeā voice often associated with traditional TTS applications.
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š®Browse our always Up-To-Date AI Tools Database.
š°FUNDING FRONTLINES
š¼WHOāS HIRING?
X (New York City, NY): Engineering Intern, Summer 2025
VAIL SYS. (Chicago, IL): Data Analyst Intern, Summer 2025
Adobe (San Francisco, CA): Machine Learning {ML} Intern, Summer 2025
HRL Laboratories (Malibu, CA): Quantum Technology Intern, Summer 2025
Hu.ma.ne (San Francisco, CA): Software Engineering Intern, Device Automation, Summer 2025
š¤PROMPT OF THE DAY
BUSINESS DOCUMENTS
šBusiness Document Compliance
Draft a [Policy/Document] for [Small Business] in [Location] that complies with [Law/Regulation].
Make sure to clearly define the purpose of the Policy or Document, identify the applicable Laws and Regulations, provide specific Guidelines and Procedures, and include a Review and Update process.
Policy/Document = [Insert Here]
Small Business = [Insert Here]
Location = [Insert Here]
Law/Regulation = [Insert Here]
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