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AI News 2024-11-19

Nov 19, 202415 min read

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Overview

The AI landscape is rapidly evolving, with major tech companies and startups alike investing heavily in AI applications for scientific research and business solutions. From Google’s $20 million fund for AI-driven scientific breakthroughs to ElevenLabs’ new conversational AI agents, these developments are reshaping how we approach complex problems across various industries.

Major Developments

Google’s $20M AI Fund

  • Launched initiative to accelerate scientific breakthroughs using AI
    • $20 million in cash grants
    • $2 million in Google Cloud credits
  • Supporting ~15 global academic and non-profit organizations by 2026
  • Focus areas:
    • Rare disease research
    • Experimental biology
    • Materials science
    • Sustainability
  • Builds on previous $200M investment over past five years

ElevenLabs Voice Cloning

  • Advanced AI models for voice replication
    • Analyzes and replicates human voices with high accuracy
    • Creates voice embeddings capturing unique characteristics
  • Features:
    • Support for 32 languages
    • Customizable parameters (speed, emotion, accent)
    • Recently added conversational AI agents
    • Interactive bot creation capabilities

Major Company Investments

  • Amazon Web Services
    • $110M in grants and cloud credits for AI researchers
  • Microsoft
    • Launched Azure AI Foundry
    • Unified enterprise AI services
    • Features Azure AI Studio and model catalog
  • Meta
    • Formed new Business AI group led by Clara Shih
    • Focus on business tools and Llama models
  • IBM & NVIDIA
    • Watson for Drug Discovery
    • NVIDIA AI Labs (NVAIL) program

Leading AI Startups

  • Iris.ai
    • $28.6M funding
    • AI Science Assistant for R&D
  • Cervest
    • ÂŁ32.7M funding
    • Climate adaptation focus
  • Bioptimus
    • $35M funding
    • Universal AI model for biology
  • Exscientia
    • $600M+ funding
    • AI-powered drug discovery
  • Consensus
    • AI search engine for scientific papers

AIRIS in Minecraft

Overview

  • Joint project by ASI Alliance and SingularityNET
  • Autonomous learning system within Minecraft environment
  • Operates without pre-set rules

Key Features

  • Real-time environmental adaptation
  • Autonomous rule generation
  • Advanced exploration capabilities
  • Object interaction potential
  • Multi-agent scenario support

Applications

  • Robotics development
  • Smart home systems
  • Autonomous system training
  • General AI advancement

Sources

  1. TechCrunch
  2. Entrepreneur
  3. Artificial Intelligence News
  4. G2
  5. SingularityNET Blog

Research

Most of this comes direct from Perplexity right here: https://www.perplexity.ai/page/ai-news-today-nFrjCuQlTEWjjKzylscwfQ

Google Commits $20M to AI Research for Scientific Breakthroughs

Google.org has announced a $20 million funding initiative to support scientists and researchers using AI for scientific breakthroughs[2]. The funding includes:

  • $20 million in cash grants
  • $2 million in Google Cloud credits

Key details:

  • Aimed at academic and non-profit institutions globally
  • Focus on using AI to address complex problems in fields like rare disease research, experimental biology, materials science, and sustainability
  • Funding to be dispersed to around 15 organizations by 2026

This move positions Google to build relationships with leading scientific minds and potential future customers requiring significant AI compute resources.

Meta Launches New Business AI Group

Meta has hired Clara Shih, former CEO of AI at Salesforce, to lead a new Business AI group[3]. The group will focus on:

  • Building AI tools for businesses using Meta’s apps (Facebook, Instagram, WhatsApp) to reach consumers
  • Making Meta’s Llama large language models accessible to businesses
  • Potentially offering AI-generated ad creation tools

This initiative aligns with Meta’s strategy of enhancing its existing apps with AI capabilities rather than selling standalone AI subscriptions.

Microsoft Unveils Azure AI Foundry

At its annual Ignite conference, Microsoft announced the Azure AI Foundry[6], which brings together several enterprise AI services under one umbrella. Key features include:

  • Azure AI Studio as the management console
  • A unified model catalog with closed and open-weight foundation models
  • New Azure AI Foundry SDK for customizing and deploying AI apps
  • 25 prebuilt app templates
  • Azure AI Agent Service for building business process automation agents (launching next month)

The Azure AI Foundry aims to streamline AI development and deployment for enterprises.

Other Notable AI News

  • ElevenLabs launched capabilities for building conversational AI agents with customizable voices and response characteristics[4].
  • C3.ai stock surged 13.2% following the announcement of a strategic partnership with Microsoft[5].
  • Security experts warn against uploading private medical images to AI chatbots due to data privacy and potential misuse concerns[7].
  • AI-powered self-publishing platform Spines claims to offer faster and cheaper book publishing services compared to traditional publishers[8].

These developments highlight the ongoing integration of AI across various industries and the continued focus on making AI tools more accessible to businesses and researchers.

Citations: [1] https://www.artificialintelligence-news.com [2] https://techcrunch.com/2024/11/18/google-org-commits-20m-to-researchers-using-ai-for-scientific-breakthroughs/ [3] https://techcrunch.com/2024/11/19/meta-hires-salesforces-ceo-of-ai-clara-shih-to-lead-new-business-ai-group/ [4] https://techcrunch.com/2024/11/18/elevenlabs-now-offers-ability-to-build-conversational-ai-agents/ [5] https://finance.yahoo.com/news/why-c3-ai-stock-popped-160121328.html [6] https://techcrunch.com/2024/11/19/microsoft-brings-together-its-enterprise-ai-offerings-in-the-azure-ai-foundry/ [7] https://techcrunch.com/2024/11/19/psa-you-shouldnt-upload-your-medical-images-to-ai-chatbots/ [8] https://techcrunch.com/2024/11/19/itching-to-write-a-book-ai-publisher-spines-wants-to-make-a-deal/

Google’s $20 million fund for AI-driven scientific research is poised to have a significant impact on scientific breakthroughs in several ways:

Accelerating Research in Key Fields

The funding initiative aims to support research at the intersection of different scientific disciplines, focusing on areas such as:

  • Rare and neglected disease research
  • Experimental biology
  • Materials science
  • Sustainability

By targeting these complex, multidisciplinary problems, Google’s fund has the potential to accelerate breakthroughs in critical areas of scientific inquiry[1][5].

Providing Essential Resources

The fund addresses several crucial needs for researchers:

  • $20 million in cash grants
  • $2 million in Google Cloud credits
  • Access to computational power
  • Access to foundational datasets
  • Cross-domain expertise[3][5]

These resources will enable scientists to leverage AI technologies more effectively in their research, potentially condensing years of work into much shorter timeframes[1].

Fostering Collaboration

Google.org plans to work with internal AI teams from Google DeepMind and Google Research, as well as external experts, to guide the allocation of funds. This collaborative approach aims to:

  • Support projects at the intersection of different scientific fields
  • Facilitate knowledge sharing between AI experts and domain scientists
  • Encourage interdisciplinary research[5]

Expanding Research Opportunities

Based on previous studies of research funding impacts, we can expect this initiative to lead to:

  • Increased publication output (approximately one additional peer-reviewed publication per year for funded researchers)
  • Higher citation rates for published work
  • More timely dissemination of research through preprints and other channels[2]

Potential Long-Term Impacts

While the immediate focus is on supporting individual research projects, the long-term effects of this funding could include:

  • Building stronger relationships between Google and leading scientific institutions
  • Positioning Google as a key provider of AI infrastructure for scientific research
  • Inspiring similar initiatives from other tech companies or research funders
  • Accelerating the integration of AI tools into standard scientific practice[3][6]

By providing both financial support and essential AI infrastructure, Google’s fund has the potential to significantly accelerate scientific breakthroughs, particularly in fields where AI can help address complex, multidisciplinary challenges.

Citations: [1] https://www.entrepreneur.com/en-in/news-and-trends/aiding-in-scientific-breakthroughs-googles-20-million/483117 [2] https://www.nature.com/articles/s41599-021-00891-x [3] https://finance.yahoo.com/news/google-org-commits-20m-ai-111701730.html [4] https://health-policy-systems.biomedcentral.com/articles/10.1186/s12961-020-00572-2 [5] https://timesofindia.indiatimes.com/technology/tech-news/google-invests-20-million-in-ai-for-science-to-transform-research/articleshow/115451766.cms [6] https://techcrunch.com/2024/11/18/google-org-commits-20m-to-researchers-using-ai-for-scientific-breakthroughs/

ElevenLabs is an innovative AI company focused on developing advanced audio and voice technologies. Here are some key aspects of their AI offerings:

Voice Synthesis and Cloning

ElevenLabs is primarily known for its high-quality AI-powered text-to-speech and voice cloning capabilities. Their technology allows users to:

  • Generate natural-sounding synthetic voices from text input
  • Clone voices with remarkable accuracy from just a few seconds of audio
  • Customize voice characteristics like pitch, speed, accent, and emotion

This technology has applications in audiobook production, content creation, gaming, and more[1][2].

Conversational AI Agents

Recently, ElevenLabs launched the ability to build conversational AI bots on their developer platform. This new feature allows users to:

  • Create complete conversational agents with customizable variables
  • Set tone of voice, response length, and other parameters
  • Integrate knowledge bases to power the bots
  • Handle customer interruptions and manage conversation flow

This expansion into conversational AI positions ElevenLabs to compete with other major players in the voice AI space[3].

Multilingual Support

ElevenLabs’ AI models can generate speech across 32 languages, making their technology valuable for content localization and global accessibility[5].

AI Audio Research

Beyond their product offerings, ElevenLabs is actively involved in AI audio research. Their team develops models for:

  • Realistic and contextually-aware speech generation
  • Voice synthesis and manipulation
  • Sound effect generation

This research drives the continuous improvement of their products and pushes the boundaries of AI audio technology[5].

Applications and Use Cases

ElevenLabs’ AI technology finds applications in various fields:

  • Content creation (videos, podcasts, audiobooks)
  • Gaming (character voices, dynamic narratives)
  • Accessibility (text-to-speech for visually impaired users)
  • Entertainment (media localization, pre-production in film)
  • Business (conversational agents, customer service)[4]

Ethical Considerations

ElevenLabs emphasizes the responsible development and use of their AI technology. They prioritize safety in the deployment of AI voices, recognizing the potential impact on digital interactions and communication[5].

ElevenLabs’ AI offerings represent a significant advancement in voice synthesis and audio generation, with potential to transform how we create, consume, and interact with audio content across various industries.

Citations: [1] https://10web.io/ai-tools/elevenlabs/ [2] https://www.g2.com/products/elevenlabsio/features [3] https://techcrunch.com/2024/11/18/elevenlabs-now-offers-ability-to-build-conversational-ai-agents/ [4] https://elevenlabs.io/use-cases [5] https://elevenlabs.io/about

ElevenLabs’ voice cloning technology works through a sophisticated process that leverages advanced AI and machine learning algorithms. Here are the key aspects of how their system functions:

Data Collection and Processing

  1. Voice Sampling: The process begins with collecting audio samples of the target voice. ElevenLabs offers two main options:

    • Instant Cloning: Requires just a few minutes of audio
    • Professional Cloning: Uses about 30 minutes of high-quality audio for superior results

  2. Data Processing: The collected audio is broken down into individual soundwaves and phonemes (the smallest units of sound in language)[5].

AI Model Training

  1. Speech Model Training: The AI analyzes the processed data to identify patterns in speech, including pitch, tone, inflection, and rhythm[5].

  2. Voice Embedding: The system creates a voice embedding - a low-dimensional representation of the voice’s characteristics, making it easier for machine learning models to work with[3].

Voice Generation

  1. Text-to-Speech Synthesis: Once trained, the model can generate new speech in the cloned voice from any text input[1].

  2. Context-Aware Modulation: ElevenLabs’ technology uses context clues to adjust delivery. For example, it can adopt a serious tone for news reports or a dramatic flair for literary passages[4].

Advanced Features

  1. Multilingual Support: ElevenLabs supports voice cloning across 29 languages, allowing the cloned voice to speak in multiple languages[7].

  2. Customization Options: Users can fine-tune various aspects of the generated voice, including tone, speed, and emotion[1].

  3. Conversational AI Integration: Recently, ElevenLabs launched the ability to build conversational AI agents using cloned voices, expanding the technology’s applications[6].

Security and Ethics

  1. Verification Process: To prevent misuse, ElevenLabs has implemented a verification process for voice cloning and limits it to paid accounts[4].

  2. Privacy Controls: The system ensures that only authorized users can clone and use a specific voice, maintaining privacy and control over digital personas[7].

ElevenLabs’ voice cloning technology stands out for its high quality, flexibility, and range of applications. It goes beyond simple replication, offering nuanced, context-aware voice generation that can be used for various purposes, from content creation to accessibility solutions.

Citations: [1] https://play.ht/blog/elevenlabs-voice-cloning/ [2] https://proceedings.neurips.cc/paper_files/paper/2018/file/4559912e7a94a9c32b09d894f2bc3c82-Paper.pdf [3] https://www.veritonevoice.com/blog/voice-cloning-101/ [4] https://www.theatlantic.com/technology/archive/2024/05/elevenlabs-ai-voice-cloning-deepfakes/678288/ [5] https://lovo.ai/post/ai-voice-cloning-what-it-is-and-how-it-works [6] https://techcrunch.com/2024/11/18/elevenlabs-now-offers-ability-to-build-conversational-ai-agents/ [7] https://elevenlabs.io/blog/what-is-voice-cloning

ElevenLabs has recently launched a new service offering that allows users to build conversational AI agents on their developer platform. This expansion represents a significant evolution of their existing voice AI technology. Here are the key aspects of this new service:

Customizable Conversational Agents

Users can now create complete AI-powered conversational bots with a high degree of customization:

  • Persona Creation: Define the agent’s primary language, first message, and system prompt to establish its personality[1][2].
  • Voice Customization: Adjust tone, speed, and other voice characteristics to match the desired interaction style[1].
  • Response Control: Set parameters like response length and creativity level (temperature)[1][2].

Integration with Language Models

The service offers flexibility in choosing and integrating large language models:

  • Model Selection: Users can choose from models like Gemini, GPT, or Claude[1][3].
  • Custom LLM Integration: Developers can integrate their own custom language models with the bot[1][3].

Knowledge Base Integration

To enhance the AI’s capabilities and domain-specific knowledge:

  • Multiple Input Options: Users can add files, URLs, or text blocks as knowledge sources[1][3].
  • Customized Information: This allows the creation of bots with specialized knowledge for specific industries or use cases.

Developer-Friendly Tools

ElevenLabs provides a range of tools to facilitate easy development and integration:

  • SDK Compatibility: Supports Python, JavaScript, React, and Swift[1][2].
  • WebSocket API: Offered for more advanced customization needs[1][2].
  • Templates: Pre-built templates are available to jumpstart the development process[2].

Advanced Features

The service includes several sophisticated capabilities:

  • Interruption Handling: The AI can manage customer interruptions during conversations[1].
  • Data Collection: Companies can define criteria to collect specific data items from customers during interactions[1].
  • Evaluation Criteria: Natural language can be used to define success or failure metrics for conversations[1].

End-to-End Solution

ElevenLabs has created a comprehensive pipeline for conversational AI:

  • Text-to-Speech: Leveraging their existing high-quality voice synthesis technology[1].
  • Speech-to-Text: Newly developed capabilities to enable two-way conversations[1][3].

This new offering positions ElevenLabs as a competitor in the conversational AI market, rivaling both established tech giants and other AI startups. The company believes its edge lies in the high degree of customization and the ability to switch between different language models, providing flexibility that some competitors may lack[1][3].

Citations: [1] https://techcrunch.com/2024/11/18/elevenlabs-now-offers-ability-to-build-conversational-ai-agents/ [2] https://www.ainews.com/p/elevenlabs-launches-tools-for-custom-conversational-ai-agents [3] https://www.aibase.com/news/13315 [4] https://web.swipeinsight.app/posts/elevenlabs-launches-conversational-ai-agents-12777

Here are some other notable AI news stories announced today:

Meta Launches New Business AI Group

Meta has formed a new Business AI group, led by Clara Shih, former CEO of AI at Salesforce. This group will focus on:

  • Developing AI tools for businesses using Meta’s apps (Facebook, Instagram, WhatsApp) to reach consumers
  • Making Meta’s Llama large language models more accessible to businesses
  • Potentially offering AI-generated ad creation tools

This initiative aligns with Meta’s strategy of enhancing its existing apps with AI capabilities rather than selling standalone AI subscriptions.

Microsoft Unveils Azure AI Foundry

At its annual Ignite conference, Microsoft announced the Azure AI Foundry, which brings together several enterprise AI services under one umbrella. Key features include:

  • Azure AI Studio as the management console
  • A unified model catalog with closed and open-weight foundation models
  • New Azure AI Foundry SDK for customizing and deploying AI apps
  • 25 prebuilt app templates
  • Azure AI Agent Service for building business process automation agents (launching next month)

The Azure AI Foundry aims to streamline AI development and deployment for enterprises.

Other AI News Highlights

  • C3.ai stock surged 13.2% following the announcement of a strategic partnership with Microsoft.
  • Security experts warned against uploading private medical images to AI chatbots due to data privacy and potential misuse concerns.
  • AI-powered self-publishing platform Spines claimed to offer faster and cheaper book publishing services compared to traditional publishers.

These developments showcase the ongoing integration of AI across various industries and the continued focus on making AI tools more accessible to businesses and researchers.

Citations: [1] https://techcrunch.com/2024/11/18/google-org-commits-20m-to-researchers-using-ai-for-scientific-breakthroughs/ [2] https://timesofindia.indiatimes.com/technology/tech-news/google-invests-20-million-in-ai-for-science-to-transform-research/articleshow/115451766.cms [3] https://finance.yahoo.com/news/google-org-commits-20m-ai-111701730.html [4] https://www.aibase.com/news/13315 [5] https://techcrunch.com/2024/11/18/elevenlabs-now-offers-ability-to-build-conversational-ai-agents/ [6] https://www.ainews.com/p/elevenlabs-launches-tools-for-custom-conversational-ai-agents

Several major companies and organizations are investing in AI for scientific research, in addition to Google’s recent $20 million commitment. Here are some notable examples:

Amazon Web Services (AWS)

AWS recently announced a significant investment in AI research:

  • $110 million in grants and cloud credits to attract AI researchers to its ecosystem
  • This initiative aims to support researchers working on various AI applications, including scientific research

Microsoft

Microsoft has been actively investing in AI for scientific research through various initiatives:

  • Azure AI platform provides tools and services for researchers
  • Partnerships with academic institutions and research organizations to advance AI in science
  • Project InnerEye, which uses AI for medical image analysis and radiotherapy planning

IBM

IBM has a long history of investing in AI for scientific research:

  • IBM Watson for Drug Discovery helps researchers analyze scientific literature and data
  • Quantum computing research that combines AI with quantum algorithms for scientific applications

NVIDIA

NVIDIA, known for its GPU technology, is heavily invested in AI for scientific research:

  • NVIDIA AI Labs (NVAIL) program partners with universities on AI research
  • Provides hardware and software tools specifically designed for scientific AI applications

Howard Hughes Medical Institute (HHMI)

HHMI, a non-profit research organization, has made a substantial commitment to AI in life sciences:

  • $500 million investment over 10 years to support AI-driven projects in life sciences
  • Focuses on placing AI at the center of the scientific process to accelerate discovery
  • Aims to create generalizable learning models capable of inferring underlying principles in biological data

National Science Foundation (NSF)

The NSF, a U.S. government agency, is also investing in AI for scientific research:

  • $20 million investment in 25 projects through the Collaborations in Artificial Intelligence and Geosciences (CAIG) program
  • Aims to advance AI techniques in geosciences and expand education and training opportunities

These investments from various companies and organizations demonstrate the growing recognition of AI’s potential to accelerate scientific breakthroughs across multiple disciplines. The trend suggests that AI is becoming an increasingly integral part of scientific research methodologies and infrastructure.

Citations: [1] https://timesofindia.indiatimes.com/technology/tech-news/google-invests-20-million-in-ai-for-science-to-transform-research/articleshow/115451766.cms [2] https://www.ai-startups.org/top/science/ [3] https://www.entrepreneur.com/en-in/news-and-trends/aiding-in-scientific-breakthroughs-googles-20-million/483117 [4] https://techcrunch.com/2024/11/18/google-org-commits-20m-to-researchers-using-ai-for-scientific-breakthroughs/ [5] https://www.hhmi.org/news/hhmi-invests-500-million-ai-driven-life-sciences-research [6] https://new.nsf.gov/news/nsf-invests-20m-advance-artificial-intelligence-technologies [7] https://finance.yahoo.com/news/google-org-commits-20m-ai-111701730.html

Based on the search results and additional information provided, several startups are leading the charge in AI for scientific research:

  1. Iris.ai
  • Country: Norway
  • Funding: $28.6M
  • Focus: AI Science Assistant to help R&D teams increase productivity when researching published scientific literature
  • Uses techniques like keyword extraction, word embeddings, and topic modeling
  1. Descartes Labs
  • Country: USA
  • Funding: $58.3M
  • Focus: Building a data refinery for satellite imagery to enable computation and analysis at global scale
  1. Cervest
  • Country: UK
  • Funding: ÂŁ32.7M
  • Focus: AI platform to help businesses, governments and growers adapt to climate volatility
  1. Bioptimus
  • Country: France
  • Funding: $35M
  • Focus: Developing a universal AI foundation model for biology
  1. PhysicsX
  • Country: UK
  • Funding: $32M
  • Focus: AI and simulation engineering technologies to reinvent machine and product design/operation
  1. Exscientia
  • Country: UK
  • Focus: AI-powered drug discovery and design platform
  • Has raised over $600M in funding
  1. Standigm
  • Country: South Korea
  • Focus: AI platform for drug discovery and design
  1. Genesis Therapeutics
  • Country: USA
  • Focus: Using neural networks and biophysical simulation for drug design and development
  1. BenchSci
  • Country: Canada
  • Focus: AI platform to empower scientists with advanced biomedical AI for more successful experiments
  1. Consensus
  • Country: USA
  • Focus: AI-powered search engine for scientific research papers

Additionally, major tech companies and research organizations are investing heavily in AI for scientific research:

  • Google: $20 million funding initiative for AI in scientific research
  • Amazon Web Services: $110 million in grants and cloud credits for AI researchers
  • Microsoft: Partnerships and tools for AI in scientific applications
  • IBM: Watson for Drug Discovery and quantum computing research
  • NVIDIA: Partnerships with universities on AI research through NVIDIA AI Labs (NVAIL)
  • Howard Hughes Medical Institute: $500 million investment over 10 years in AI-driven life sciences research

These startups and initiatives demonstrate the growing importance and potential of AI in accelerating scientific discovery across multiple disciplines.

Citations: [1] https://www.ai-startups.org/top/science/ [2] https://www.analyticsinsight.net/startups/top-100-promising-ai-startups-in-2024 [3] https://www.greyb.com/blog/ai-drug-discovery-startups/ [4] https://www.hhmi.org/news/hhmi-invests-500-million-ai-driven-life-sciences-research [5] https://wellfound.com/startups/industry/science-4

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