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AI's 3D Mastery, Pharma Breakthroughs, Creating Music Videos In An Hour and Much More!

Uncover AI’s power in transforming 3D animations, pioneering new drugs, and reshaping tech with today’s essential developments and strategic insights.

Author

Brent Moreno
March 20, 2024

TL;DR 📌:

  1. 3D Animation Redefined: StabilityAI's Stable Video 3D model turns images into lifelike animations, enhancing virtual reality and digital media.

  2. Roblox's Creative Revolution: New AI-powered 3D modeling tools automate character and texture creation, sparking debate on creative ethics.

  3. Pharma's AI Triumph: Insilico Medicine's AI-designed drug enters human trials, a groundbreaking stride in AI-assisted pharmaceuticals.

  4. Intel's Big Bet: $8.5 billion U.S. funding propels Intel's AI chip manufacturing, aiming to secure America's tech leadership.

  5. Linguistic Insights: AI chatbot models process multiple languages with an English-centric approach, raising cultural adaptation challenges.

  6. Fitness Innovation: Google and Fitbit's AI personal trainer melds technology with personal health, shaping future fitness regimes.

  7. Voice for Hire: Voice-Swap's novel approach treats artists' AI voices as assets, exploring new frontiers in music and monetization.

  8. Learning Like Humans: An OpenAI spinoff achieves a breakthrough in AI learning, simulating human observational learning processes.

  9. Tutorial Spotlight: Create an AI music video in under an hour, merging creativity with AI efficiency.

  10. Research Focus: TnT-LLM framework demonstrates AI's prowess in text mining, offering scalable solutions for data-driven insights.

  11. Toolbox Essentials: Explore innovative AI tools enhancing productivity in coding, storytelling, customer research, and scheduling.

  12. Tweet Wisdom: Linus Ekenstam's take on AI's role in job interviews, hinting at a future where AI representations could face real-world tasks.

StabilityAI's Breakthrough: Stable Video 3D Model Transforms Images into Dynamic Animations

Quick Bytes: StabilityAI introduces a groundbreaking AI model, Stable Video 3D (SV3D), capable of transforming static images into dynamic 3D animations, signaling a leap towards the realization of virtual environments akin to the science fiction concept of a holodeck. Building on the foundations of Stable Video Diffusion and leveraging a vast dataset, SV3D offers enhanced depth and realism in video generation, promising innovative applications in various sectors while also navigating the complexities of digital authenticity and data transparency.

Key Takeaways:

Innovative 3D Animation: StabilityAI's SV3D model generates three-dimensional animations from single images, offering a new level of depth in AI-generated content.

Technological Advancement: SV3D builds upon previous models, showcasing advancements in AI's ability to create complex, multi-view animations.

Potential Applications: The technology has implications for product visualization, virtual reality, and enhancing digital media with interactive 3D elements.

Training and Transparency: StabilityAI utilizes the Objaverse dataset for training SV3D, maintaining openness about its data sources and adhering to ethical licensing practices.

Future Possibilities: The development of SV3D hints at a future where virtual and augmented reality can merge seamlessly, creating immersive digital experiences.

The Big Picture: StabilityAI's Stable Video 3D represents a significant stride in AI-driven media creation, pushing the boundaries of how we perceive and interact with digital content. As this technology continues to evolve, it could redefine the landscape of digital media, virtual reality, and interactive environments, bridging the gap between imagination and reality. The advent of SV3D and similar models heralds a new era of digital innovation, where the virtual worlds envisioned in science fiction become tangible and integral to our digital experience.

Roblox Unveils AI-Driven 3D Modeling Tools to Revolutionize Content Creation

Image Credit: Roblox Studio

Quick Bytes: Roblox has introduced new AI-powered tools for 3D modeling, aiming to simplify the creation process for its vast community of developers. The Avatar Auto Setup and Texture Generator tools are designed to automate rigging and texture creation, respectively, significantly reducing the time and effort needed to bring 3D models to life on the platform. While these advancements promise to enhance creative possibilities, they also spark discussions about the ethical implications of such technology, particularly in light of recent criticisms regarding labor practices.

Key Takeaways:

Innovative AI Tools: Roblox's new AI technologies, Avatar Auto Setup and Texture Generator, streamline the 3D modeling process, facilitating easier and faster creation of animated characters and textured objects.

Enhanced Creative Efficiency: These tools are designed to reduce the time-consuming aspects of 3D modeling, offering rapid rigging and texture generation based on simple text prompts.

Empowering Creators: Roblox aims to democratize the creation process, allowing users of varying skill levels to contribute content to the platform.

Controversy and Criticism: The introduction of these tools occurs amid broader debates about the platform's labor practices, especially concerning its younger user base.

Access and Availability: Both Avatar Auto Setup and Texture Generator are now accessible in Roblox Studio, offering immediate benefits to creators on the platform.

The Big Picture: Roblox's launch of AI-powered 3D modeling tools represents a significant step forward in the platform's capabilities, potentially transforming how content is created and shared. By automating complex processes, these tools can empower a broader range of creators to participate in the digital economy. However, the move also underscores the need for careful consideration of the ethical and labor-related implications of such technologies, particularly in platforms heavily utilized by younger demographics. As Roblox continues to innovate, the balance between technological advancement and responsible community engagement remains a critical focus.

Insilico Medicine's AI-Driven Drug Advances to Human Trials, Marking Pharmaceutical Milestone

Quick Bytes: Insilico Medicine, under the leadership of Alex Zhavoronkov, has reportedly developed a groundbreaking AI-driven drug aimed at treating idiopathic pulmonary fibrosis, marking a significant milestone in the field of AI-assisted pharmaceuticals. This development highlights the evolving role of AI in drug discovery, showcasing the potential for AI to not only identify cellular targets but also design the chemical structure of new drugs, potentially revolutionizing the pharmaceutical industry.

Key Takeaways:

  • AI-Driven Drug Development: Insilico Medicine claims to have created the first "true AI drug," showcasing AI's potential in accelerating the drug development process.

  • Innovative Approach: The company utilized AI to identify cellular targets and design the drug's chemical structure, representing a significant advancement in AI applications in biotechnology.

  • Phase II Clinical Trials: The AI-generated drug has entered Phase II trials, testing its efficacy in treating idiopathic pulmonary fibrosis, a serious lung condition.

  • Broader Implications: This milestone reflects the growing impact of AI on the pharmaceutical industry, promising faster and potentially more innovative drug discovery processes.

  • Debate on AI's Role: The claim of developing the first true AI drug sparks discussions on the definition and impact of AI in drug development, with perspectives varying across the industry.

The Big Picture: Insilico Medicine's achievement in advancing an AI-generated drug to clinical trials exemplifies the transformative potential of AI in the pharmaceutical sector. This innovation not only accelerates the drug discovery process but also opens new avenues for treating complex diseases. As AI continues to integrate into pharmaceutical research, it heralds a new era where drug development is faster, more efficient, and possibly more effective, aligning with broader trends in digital biology and AI-driven innovation in healthcare.

Intel Secures $8.5 Billion in U.S. Funding to Expand Domestic Chip Manufacturing

Quick Bytes: Intel is poised to receive a substantial $8.5 billion in U.S. government grants, with an additional $11 billion in loans, to enhance semiconductor manufacturing domestically. This financial boost, part of the Biden administration’s strategy to advance U.S. production of AI-focused chips, will support Intel's expansion in Arizona and Ohio, and research facilities in Oregon and New Mexico. The initiative aims to reinforce American leadership in technological innovation and create thousands of jobs, signaling a significant investment in the future of U.S. semiconductor manufacturing.

Key Takeaways:

  • Major Government Investment: Intel's semiconductor expansion is backed by $8.5 billion in grants and $11 billion in loans from the U.S. government, underlining the strategic importance of domestic chip production.

  • Focus on AI and Advanced Semiconductors: The funding supports Intel’s efforts to advance in the AI semiconductor market, aiming to enhance America's competitive edge in global technology.

  • Job Creation and Economic Impact: Intel’s expansion is set to generate approximately 20,000 construction jobs and 10,000 manufacturing positions, contributing significantly to economic growth.

  • Strategic Locations for Development: Investments will be channeled into state-of-the-art manufacturing sites in Arizona and Ohio, with additional support for research and development in Oregon and New Mexico.

  • Legislative Support: The financial backing is part of the 2022 Chips and Science Act, reflecting a broader legislative effort to boost the U.S. semiconductor industry.

The Big Picture: Intel's significant financial backing from the U.S. government marks a pivotal moment in the national strategy to reclaim and secure leadership in semiconductor manufacturing, particularly in the AI sector. This move not only aims to reduce dependence on overseas chip production but also stimulates job creation and technological advancement. As the U.S. invests heavily in the semiconductor industry, the global landscape of tech innovation and production is set to shift, with potential long-term benefits for America's economic and strategic position in the world of advanced technology.

AI chatbot models ‘think’ in English even when using other languages

When answering questions posed in Chinese, French, German or Russian, large language models seem to process the queries in English, which could create cultural issues

Google and Fitbit are building an AI personal trainer

AI-based personalized coaching is coming.

Why Voice-Swap Wants to Be an ‘Agency’ for Artists’ AI Voices

AI music company Voice-Swap wants to monetize artists' AI voices, say founders Dan "DJ Fresh" Stein and Michael Pelczynski in a new interview.

Robots can learn like humans thanks to OpenAI spinoff

Using a vast amount of data, the model can learn through observation.

Make An AI Music Video In Under An Hour

Authors: Mengting Wan, Tara Safavi, Sujay Kumar Jauhar, Yujin Kim, Scott Counts, Jennifer Neville, Siddharth Suri, Chirag Shah, Ryen W. White, Longqi Yang, Reid Andersen, Georg Buscher, Dhruv Joshi, Nagu Rangan

Executive Summary:

The paper introduces TnT-LLM, a framework utilizing Large Language Models (LLMs) for text mining, focusing on taxonomy generation and text classification. It streamlines the process of converting unstructured text into organized, meaningful categories, which is traditionally labor-intensive and requires domain expertise. TnT-LLM operates in two phases: generating a label taxonomy through zero-shot multi-stage reasoning and then classifying text based on this taxonomy to create training data for lightweight classifiers. The methodology was tested on Bing Copilot data, demonstrating TnT-LLM's ability to produce accurate and relevant taxonomies and efficiently classify large-scale text with minimal human intervention.

Pros:

- TnT-LLM automates and scales the process of taxonomy generation and text classification, reducing the need for domain expertise.

- Demonstrates high accuracy and relevance in label taxonomy creation compared to state-of-the-art methods.

- Facilitates large-scale text classification efficiently, making it suitable for processing vast amounts of data quickly.

- Provides a modular approach, adaptable to various use cases and text corpora.

Limitations:

- The study's reliance on LLMs could raise concerns about computational costs and the environmental impact of training and deploying such models.

- Potential bias in LLM-generated labels and classifications necessitates careful evaluation and calibration.

- The framework's performance may vary depending on the complexity and specificity of the text corpus and use case.

Use Cases:

- Text mining for user intent and conversational domain analysis in chat-based search engines or customer service bots.

- Structuring and analyzing large text corpora in various languages and domains, facilitating knowledge discovery and decision-making.

- Enhancing data labeling processes for machine learning model training with minimal human intervention.

Why You Should Care:

TnT-LLM represents a significant advancement in text mining, offering a scalable and efficient solution for processing large datasets. By leveraging the capabilities of LLMs, it reduces the need for manual labor and expert knowledge, making text mining more accessible and practical for a wide range of applications. This innovation could transform how organizations handle and derive value from their textual data, leading to more informed decisions and strategies.

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Write Irresistible Personal Tweets:

I want you to write "irresistible personal tweets" for me. 

These tweets are characterised by being extremely original and unique. They always include one reference, fact, opinion, or experience by the author.

Come up with uncommon, varied results.

For context, [1.INSERT CONTEXT]

My audience consists of [2. GIVE AUDIENCE CONTEXT]

Here are some examples of "irresistible personal tweets", separated by [NEW TWEET]:

[NEW TWEET]:
People's attention spans are FUCKED.

This is why I created a SUPER basic landing page for my course waitlist.

My thoughts:

Give them a short, bite-size overview instead of a long sales page.

Write everything like a tweet.

Result :

The landing page converts at almost 80%.

[NEW TWEET]:

I battled with anxiety throughout most of my life.

I fucked up life-changing money on FTX.

I changed my career 2 times before seeing any success.

I wake up often doubting if I can do it.

But I just don't give up.

If I can make shit happen, you can too.

[NEW TWEET]:

I posted 20,000 times before I got my first client.

[NEW TWEET]:

If you could choose between two teachers:

1. The Natural
2. The Non-Natural

And they're both equally skilled,

I'd go with the Non-Natural.

A Natural is good at the talent but can struggle teaching it.

A Non-Natural is a great teacher because he wasn't born with the talent.

[NEW TWEET]:

Some premium Twitter bro advice I’ve seen lately: 

• Smoke cigs to focus
• Take 4 hour ice baths 
• Stare at the sun for energy

Have a day off

What’s is going to be next?

“Inhale paint fumes for creativity”

[NEW TWEET]:
You make money.
People say you're scamming.

You get jacked.
People say you're on roids.

You grow a following.
People say you bought 'em.

People will talk shit regardless, so do whatever the fuck makes you happy.

[NEW TWEET]:
I escaped the matrix and made a full-time online income when I was 23.

I achieved it by doing the opposite of my peers.

I chose self-education over college.

I paid for mentors instead of a new car.

I prioritized building instead of partying.

A few life-changing choices.


-

Here are some past tweets I've written, separated by [NEW TWEET]:

[3. INSERT YOUR TWEETS]

----

Now, do this:

1) Learn what tone of voice and structure characterises "irresistible personal tweets"
2) Learn my tone of voice from my past tweets
3) Learn about me & my experiences from my past tweets
5) Based on the constraints I gave you, write 20 new "irresistible personal tweets" in my tone of voice for me

Constraints for the tweets:

1 No hashtags
2 No emojis
3 Include at least 1 personal reference, fact, or experience
4 Use complete sentences
5 Must be shorter than 280 characters
6 no questions