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AI Education Bill, TikTok's Ad Tools, and AI in Lending
Exploring new AI education initiatives, TikTok's AI-powered advertising tools, and how AI is making lending fairer.


Aideations: Your Quick Guide to Today's Top AI News
Good Morning, Innovators!
Here's what you need to know today in the world of AI and tech. We've got insights on a new AI education bill, TikTok's AI-powered ad tools, an AI-driven educational controversy, and more. Let's dive in!
🧠 Top Stories & Opinions
New Bipartisan Bill Aims to Supercharge AI Education and Workforce Training in the U.S.
TikTok Unveils New AI-Powered Ad Tools to Boost Creativity and Efficiency
Emory University Suspends Student for AI Tool That Won Their Own Contest
How AI is Making Fair Lending a Reality
🔍 News from the Front Lines
How a $10,000 Investment in AI Transformed My Career and Business Strategy
Autonomous shipping startup Orca AI tops up with $23M led by OCV Partners and MizMaa Ventures
Ex-Google CEO says the US and China's most powerful AI systems may one day be stored in military bases and surrounded by machine guns
People are dunking on Google search AI's nonsensical answers
📚 Tutorial of the Day
📝 Research of the Day
🎥 Video of the Day
⚙️ Tools of the Day
💡 Prompt of the Day
🐦 Tweet of the Day
Stay informed and ahead of the curve with Aideations. See you tomorrow for more insights and innovations! 🚀

Quick Byte:
Senator Maria Cantwell has introduced the NSF AI Education Act of 2024, a bipartisan bill designed to enhance American expertise in AI and quantum computing through scholarships, research grants, and new Centers of Excellence.
Key Takeaways:
Senator Cantwell and Senator Moran Collaboration: The bipartisan measure, proposed by Democrat Maria Cantwell and Republican Jerry Moran, aims to address the growing demand for AI expertise.
NSF AI Education Act of 2024: Focuses on AI and quantum computing education, including undergraduate and graduate scholarships, professional development fellowships, and AI research grants.
Centers of Excellence: Establishing AI “Centers of Excellence” at community colleges to develop instructional materials and collaborate with educators.
K-12 Education: Developing tools and guidance for students to use AI in K-12 classrooms.
NSF Grand Challenges: Launching an initiative to educate at least 1 million workers in AI by 2028, with a focus on underrepresented groups such as women and rural residents.
Bigger Picture:
The NSF AI Education Act of 2024 represents a significant push to prepare the U.S. workforce for the future of AI and quantum computing. By providing scholarships, research grants, and creating Centers of Excellence, the bill aims to democratize access to advanced technology education and ensure that a diverse range of students and professionals can participate in this rapidly evolving field. With support from major tech companies like Microsoft and backing from educational institutions, this legislation could be a game-changer in addressing the AI skills gap and fostering innovation. As the U.S. competes globally in AI and quantum technologies, these efforts will be crucial in maintaining leadership and driving economic growth.


Quick Byte:
TikTok is expanding its AI capabilities with a suite of new tools designed to help brands create ads more efficiently. The highlight? An AI video-generator that simplifies the ad-making process.
Key Takeaways:
TikTok Symphony: A new creative suite that includes an AI video-generator to streamline the creation of TikTok ads.
AI Assistant: Symphony also includes an AI assistant to help advertisers manage their campaigns.
TikTok One: A centralized marketing hub designed to enhance business productivity and ad performance.
Predictive AI: New performance solutions to help advertisers optimize outcomes like sales, leads, and app installs.
Ad Effectiveness: 61% of users have made purchases on TikTok or after seeing ads on the app.
User Trends: TikTok is a popular research tool, with 52% of users looking up cars and 59% deciding on game downloads via the platform.
Bigger Picture:
TikTok's latest AI-driven tools are set to revolutionize the advertising landscape, offering brands innovative ways to create, manage, and optimize their campaigns. By leveraging AI to enhance productivity and effectiveness, TikTok Symphony aims to make the ad creation process both simple and efficient. Despite ongoing legal challenges and potential layoffs, TikTok's commitment to providing cutting-edge solutions underscores its role as a major player in the digital marketing arena. As AI continues to transform how businesses interact with consumers, TikTok's new tools could become indispensable for brands looking to thrive in the competitive social media landscape.

Quick Byte:
Emory University awarded Eightball, an AI study aid tool, the $10,000 grand prize in an entrepreneurial pitch competition. Now, they’ve suspended the student creators for potentially enabling cheating, sparking a lawsuit and raising questions about AI's role in education.
Key Takeaways:
The Tool: Eightball, created by Emory undergrads, turns coursework into study aids like flashcards and practice tests.
The Win: The tool won Emory’s pitch competition last year, earning $10,000 and university promotion.
The Suspension: The creators, Benjamin Craver and his co-founder, now face suspension over concerns that Eightball "may" have been used to cheat.
The Lawsuit: Craver filed a lawsuit against Emory, challenging the suspension that affects his graduation and future plans.
The Concerns: Emory’s Honor Council cited the tool’s integration with Canvas as a "major concern," leading to allegations that Eightball was built with the intent to enable cheating.
The Broader Issue: The case highlights the challenges of keeping AI tools safe and accountable in educational settings.
Bigger Picture:
Emory University’s decision to suspend the creators of Eightball, an AI tool they initially celebrated, underscores the tension between innovation and academic integrity. While AI tools like Eightball offer significant educational benefits, they also pose risks of misuse. This incident raises critical questions about how educational institutions should balance the promotion of technological innovation with the need to maintain academic standards. As AI continues to evolve, the challenge will be to develop robust frameworks that ensure these tools are used ethically and effectively.


Quick Byte:
Artificial intelligence is tackling financial inequality by streamlining mortgage applications and eliminating biases, helping more people achieve the dream of homeownership.
Key Takeaways:
The Crisis: Affordable housing is out of reach for many, with financial inequality exacerbating the issue.
Bias in Lending: Banks and mortgage companies favor straightforward applications, disadvantaging minority groups with complex financial situations.
AI to the Rescue: Augmented AI, like AngelAi, simplifies complex applications, increasing mortgage acceptance rates by up to 50% for some groups.
Empathetic Technology: AI technology incorporates over 100 languages, making the loan application process more inclusive and user-friendly.
Economic Impact: Easier access to financial resources can incentivize developers to build more affordable housing.
Unbiased Decisions: AI can provide immediate, unbiased credit analyses, ensuring fairer loan product recommendations.
Non-judgmental Interaction: AI chatbots offer a non-intimidating, empathetic experience, reducing barriers for minorities and people with disabilities.
Financial Education: AI-driven financial literacy programs can help close the wealth gap by providing accessible education and resources.
Bigger Picture:
Artificial intelligence is revolutionizing the lending industry, making it more inclusive and fairer. By simplifying complex mortgage applications and eliminating biases, AI tools like AngelAi are helping more people secure home loans and achieve long-term wealth through homeownership. This technological advancement not only addresses systemic issues within financial institutions but also paves the way for a more equitable future. As AI continues to evolve, it holds the promise of transforming the housing market, empowering individuals with the knowledge and resources they need to manage their financial futures effectively.


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Authors: Ting Jiang, Shaohan Huang, Shengyue Luo, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang, Deqing Wang, Fuzhen Zhuang
Institutions: Beihang University, Microsoft Corporation
Summary:
The paper introduces MoRA, a new method for fine-tuning large language models (LLMs) that improves upon the current standard, Low-Rank Adaptation (LoRA). By employing high-rank updates while maintaining the same number of trainable parameters, MoRA achieves better performance in memory-intensive tasks and comparable results in others.
Why This Research Matters:
Fine-tuning large language models can be resource-intensive. LoRA has been a popular solution, updating a small portion of parameters to reduce computational costs. However, it struggles with tasks that require memorizing new knowledge. MoRA addresses this by using a high-rank updating mechanism, potentially revolutionizing how LLMs are fine-tuned for various applications.
Key Contributions:
MoRA Methodology: Introduces a square matrix for high-rank updates, improving over LoRA's low-rank matrices while keeping the parameter count constant.
Non-Parameter Operators: Develops operators to adjust input and output dimensions, ensuring compatibility with LLMs.
Comprehensive Evaluation: Tests MoRA on tasks like instruction tuning, mathematical reasoning, and continual pretraining, demonstrating superior performance in memory-intensive tasks and similar performance in others.
Use Cases:
Model Optimization: Enhancing the efficiency and effectiveness of fine-tuning processes for large language models.
Memory-Intensive Tasks: Significant improvements in tasks that require the model to learn and retain new information, such as continual pretraining in specific domains.
Broader Applicability: Potential use in various industries where large language models need to be adapted quickly and efficiently to new tasks.
Impact Today and in the Future:
Immediate Improvements: Provides a more effective method for fine-tuning LLMs, leading to better performance in memory-demanding applications like personalized AI assistants or domain-specific models.
Long-Term Evolution: Sets the stage for future research in parameter-efficient fine-tuning, potentially reducing the computational burden and cost of adapting large models to new tasks.
Theoretical Insights: Challenges the current understanding of low-rank adaptation, opening new avenues for optimizing model updates and improving performance.
MoRA is a game-changer, offering a smarter, more efficient way to fine-tune those massive language models we rely on. With better performance and lower costs, MoRA is set to make waves today and pave the way for even greater advancements tomorrow!


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CreateAICourse - Creator tool to simplify the online course creation process.
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Scaling Strategy GPT:
Scaling Strategy GPT
CONTEXT:
You are Scaling Strategy GPT, a consultant known for assisting businesses in scaling their operations effectively. Your expertise in identifying scalable opportunities and structuring growth strategies helps businesses expand sustainably and profitably.
GOAL:
Develop a plan with five key strategies to scale your business. These strategies should enable you to expand your client reach, increase your service or product offerings, and enhance operational efficiency, all while maintaining or improving the quality of your services.
DIFFERENTIATION OPPORTUNITIES CRITERIA:
Balanced Growth Approaches: Strategies should consider both horizontal and vertical growth opportunities, ensuring a balanced approach to scaling.
Resource Efficiency: Focus on maximizing existing resources and strategically acquiring new resources to support growth without overextension.
Innovative Growth Methods: Provide unique and innovative methods for scaling that are tailored to your business’s specific industry and market conditions.
Actionable and Structured: Each strategy should include detailed, actionable steps that can be implemented in a phased or immediate approach, depending on the business's readiness and market conditions.
Risk Assessment: Include a consideration of potential risks associated with scaling and propose mitigation strategies to manage these risks effectively.
Sustainability and Quality Control: Ensure that strategies address the maintenance of quality during expansion and incorporate sustainable practices as part of the growth process.
INFORMATION ABOUT YOUR BUSINESS:
(Please provide detailed information about your business to tailor the strategies effectively.)
Business Type: [Describe your business type and main offerings]
Current Operations: [Detail current operational scope and capacities]
Market Position: [Describe your current market position and competitive landscape]
Growth Targets: [Outline specific growth targets or objectives you wish to achieve through scaling]
RESPONSE FORMATTING:
Please format your response using Markdown. Clearly outline each scaling strategy with bullet points, detailing the approach, expected outcomes, and steps for implementation.

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