Fighting Superbugs with AI

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If only AI had been this progressive during Covid :/ 

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AI IN MEDICINE

🤩AI Breakthrough in Antibiotic Research
^{Insights from The Guardian}

Scientists have leveraged AI to predict new antibiotics, marking a significant advance in combating antibiotic resistance.

The Decode:

Study and Algorithm:

• A study published in Cell utilized machine learning to explore the global microbiome, uncovering nearly 1 million new molecules within microbial dark matter.
  

• The AI algorithm dramatically speeds up the discovery process, making discoveries in hours instead of years.

Public Health Urgency:

• Antimicrobial resistance caused over 1.2 million deaths in 2019, projected to rise to 10 million annually by 2050 (WHO).

Validation and Biosecurity:

• Researchers synthesized and tested 100 molecules, finding 79% effective against at least one microbe.
  

• Precautions were taken to ensure these molecules do not self-replicate.

Data Sharing and Development Timeline:

• The study's data and code are publicly available to advance scientific research.
  

• Developing these antibiotics will require years of study, including laboratory research and clinical trials, typically taking 10 to 20 years.

AI and Antibiotic Research:

• César de la Fuente has been using AI in antibiotic research for about a decade, significantly accelerating the discovery process.

Future Steps and Broader AI Applications:

• Further investigation and potential clinical trials are needed to develop these molecules into usable antibiotics.
  

• The success of this study highlights AI's potential in biology, similar to Google DeepMind's AlphaFold, which predicts protein interactions.

This study represents the largest antibiotic discovery effort to date, demonstrating AI’s potential to revolutionize drug discovery and address antibiotic resistance. It underscores the collaborative potential between AI and human researchers in accelerating scientific breakthroughs.

AI’s role in antibiotic research exemplifies its transformative impact on science, significantly speeding up the discovery process and uncovering new molecules to combat antimicrobial resistance, potentially saving millions of lives.

TOGETHER WITH AE STUDIO

85% of all AI Projects Fail, but AE Studio Delivers

If you have a big idea and think AI should be part of it, meet AE.

We’re a development, data science and design studio working with founders and execs on custom software solutions. We turn AI/ML ideas into realities–from chatbots to NLP and more.

Tell us about your visionary concept or work challenge and we’ll make it real. The secret to our success is treating your project as if it were our own startup.

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ANTIITRUST INVESTIGATION

🔍 Antitrust Investigations Target Microsoft, OpenAI, and Nvidia
^{Insights from The Verge}

The FTC and DOJ have initiated antitrust investigations into Microsoft, OpenAI, and Nvidia, examining the influence of their investments and partnerships on AI market competition and innovation.

The Decode:

FTC Investigation:

• Companies Involved: Alphabet, Amazon, Anthropic, Microsoft, and OpenAI.
  

• Purpose: Evaluate the impact of significant tech investments on the AI market.
  

• Focus Areas:
  

  • Influence of investment agreements on product releases and oversight.
    

  • Effects on market share, competition, and sales growth.
    

  • Resource competition for AI product development.
    

  • Information shared with other government bodies.

Timeline: 45 days for companies to respond.

Company Reactions:

• Microsoft: Emphasizes that partnerships like those with OpenAI foster competition and innovation.
  

• Google: Supports the FTC's investigation to shed light on customer-locking practices.

Investment Highlights:

• Microsoft and OpenAI: Microsoft, a major investor in OpenAI, has invested $10 billion and joined OpenAI’s board as a nonvoting observer.
  

• Amazon and Anthropic: Amazon invested $4 billion in Anthropic, while Google holds a 10% stake after a $300 million investment.
  

• AI Developer Partnerships: AI developers collaborate with cloud providers like Google, Microsoft, and Amazon for cost-effective access to GPUs and processors essential for training large language models.

Government Concerns:

• FTC and DOJ Debate: Agencies debated over who would lead the investigation into OpenAI and Microsoft.
  

• FTC Chair Lina Khan’s Statement: Stressed the importance of preventing tactics that could hinder competition and innovation in the growing AI market.

Background Investigations:

• FTC’s Initial Probe into OpenAI: The FTC previously investigated OpenAI, seeking documents to assess potential consumer harm from false information generated by ChatGPT.

The FTC and DOJ's investigations into Microsoft, OpenAI, and Nvidia reflect growing concerns about the power of major tech companies in the AI sector. These inquiries aim to ensure fair competition and foster innovation, potentially reshaping the future of AI development.

AI VIEWS

👀 AI Models Show Diverging Views on Controversial Issues
^{Insights from Tech Crunch}

A recent study highlights significant discrepancies in how different generative AI models handle polarizing topics, reflecting inherent biases in their training data. Researchers from Carnegie Mellon, the University of Amsterdam, and Hugging Face presented their findings at the 2024 ACM Fairness, Accountability, and Transparency (FAccT) conference.

The Decode:

Study Overview:

• Objective: Analyze AI model responses on controversial subjects like LGBTQ+ rights, social welfare, and surrogacy.
  

• Models Tested: Meta’s Llama 3, Mistral’s Mistral 7B, Cohere’s Command-R, Alibaba’s Qwen, and Google’s Gemma.
  

• Languages Used: English, French, Turkish, and German.

Discrepancies and Biases:

• Inconsistent Responses: Models provided varying answers to the same questions, indicating training data biases.
  

• High Refusal Rates: Questions on LGBTQ+ rights had the highest refusal rates. Other sensitive topics like immigration and disability rights also saw high refusal rates.
  

• Cultural and Linguistic Variations: Responses varied significantly based on language and cultural context.

Model-Specific Observations:

• Alibaba’s Qwen: Highest refusal rate, likely due to political pressures in China.
  

• Mistral: Fewer refusals, reflecting different development choices.

Implications:

• Bias in Annotations: Biases may stem from the biases of human annotators labeling the training data.
  

• Opposing Views: Models expressed contradictory views on topics like immigrant asylum in Germany and LGBTQ+ rights in Italy.

Call to Action:

• Rigorous Testing: Developers should rigorously test AI models for cultural and social biases before deployment.
  

• Comprehensive Evaluations: More thorough evaluations are needed to understand AI models' social impacts.

The study underscores the complexities and challenges in developing unbiased AI models. It highlights the critical need for ongoing scrutiny and improvement in AI development to ensure equitable and accurate responses across diverse cultural and linguistic contexts.

TOOLS YOU CANNOT MISS

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🗒️Tablepad - Tablepad is an AI-powered tool that enables users to upload, view, and query data in a simplified manner. It is designed to deliver data insights and generate charts without requiring coding skills.

🤖PrometAI  - PrometAI is an online artificial intelligence tool that enables creation of detailed business plans. It is designed to assist users through each stage of business plan development, providing a comprehensive framework that lays the foundation for growth.

📥ZeroInbox - Zero Inbox AI Email Organizer is a tool that assists users in efficiently managing their email inboxes. Its primary function is to help clear unnecessary emails, organize the inbox, thus reaching 'Inbox Zero' quickly.

HOT NEWS

📝 Google Enhances NotebookLM for Better Note-Taking

Google updates NotebookLM, allowing users to upload Google Slides and web URLs alongside Google Docs, PDFs, and text files. The new Notebook Guide generates study guides, FAQs, and briefing documents. Running on Gemini 1.5 Pro, it answers questions about charts, images, and diagrams. NotebookLM is available in over 200 countries and supports more than 100 languages.

🚀 Mistral Unveils New Services and SDK for Model Fine-Tuning

French AI startup Mistral is launching new services and an SDK to help developers and enterprises fine-tune their generative models. The Mistral-Finetune SDK allows self-service fine-tuning on various hardware setups. For managed solutions, Mistral offers fine-tuning services via API, currently supporting Mistral Small and Mistral 7B models. Custom training services are available to select customers for highly specialized models.

🌊 Google Turns to AI to Save Coral Reefs

Google developes an AI tool, SurfPerch, to help marine biologists study coral reefs. Created with Google Research and DeepMind, SurfPerch analyses thousands of hours of reef audio recordings to "hear reef health," track nocturnal activity and monitor deep or murky reefs. Public contributions to the Calling in Our Corals project helped train SurfPerch, enhancing reef conservation efforts globally.  

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