Edition 17: Microsoft Meltdown: AI's Wake-Up Call
Welcome to the AviaryAI Newsletter!
Thanks for joining us as we explore the intersection of GenAI and finance with practical learnings and the latest relevant insights. Let’s get started.
This week you’ll learn:
- 🌪️ Microsoft update causes global tech storm
- 📈 AI budgets set to skyrocket in 2025, says EY survey
- 🏦 VC firm's unique approach to AI startup investments
- 📺 YouTube content secretly fuels AI training
- 🧭 Navigating AI policy creation for credit unions
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GENERATIVE AI THIS WEEK
The coolest things we're watching and why you should care
Global Chaos Erupts from Microsoft Outtage
A flawed update from cybersecurity firm CrowdStrike caused widespread chaos for Microsoft Windows users worldwide, affecting critical services like airlines, hospitals, and emergency response systems. The incident exposed the vulnerability of global tech infrastructure heavily reliant on Microsoft's operating system.
So what?
This incident highlights the need for diversity in critical systems. Implementing AI solutions from multiple vendors or open-source projects could create a more resilient infrastructure, reducing the risk of a single point of failure.
Leading VC Uses AI Chip Stockpile as Leverage in Startup Deals
Venture capital firm Andreessen Horowitz is stockpiling thousands of coveted AI chips, including Nvidia's H100 GPUs, to rent to AI startups in exchange for equity. This move comes amid a severe shortage of AI chips, with demand far outstripping supply, forcing even tech giants to seek alternatives.
So what?
As AI becomes more integral to various industries, we may see a paradigm shift in how we view and value computational resources. This could lead to the development of new economic models and metrics, where a company's potential is measured not just by its intellectual property or market share, but also by its access to and efficient use of AI computing power.
AI Giants Caught Using YouTube Content Without Permission
Apple, Nvidia, Anthropic, and other major AI companies have been found using subtitles from over 173,000 YouTube videos to train their AI models without creators' consent. This data, part of a larger dataset called "The Pile," includes content from popular YouTubers, educational channels, and even deleted videos, raising concerns about copyright infringement and ethical data usage.
So what?
AI's potential benefits cannot overshadow the ethical implications of its training data. Credit unions have a unique opportunity to differentiate themselves by championing ethical AI practices. Consider developing an "AI Ethics Checklist" for vendor selection, emphasizing transparent data sourcing. This approach not only mitigates risks but also aligns with credit unions' member-first values, potentially becoming a powerful marketing tool in an increasingly AI-driven financial landscape.
Read the full story here.
THE AI EXECUTIVE'S HANDBOOK
One simplified GenAI concept per week to build your AI Acumen
Crafting Your Credit Union’s AI Policy
A well-crafted AI policy isn't just a check-box item — it's a must for any credit union serious about harnessing this technology responsibly.
We’ve worked with our credit union partners to identify the 3 most critical considerations for your AI policy:
1. Strategic Alignment
- How will AI support your mission and values? Consider specific use cases that enhance member experience or operational efficiency without compromising your core principles.
- Does your policy future-proof your AI initiatives? Anticipate how your AI strategy may need to evolve and build in flexibility to adapt to changing member needs, regulations, and technological advancements.
2. Ethical Use and Risk Mitigation
- How will you ensure fair, unbiased, and transparent AI decision-making? Establish clear guidelines and auditing processes to regularly assess AI models for potential biases or discriminatory outcomes.
- What safeguards will you put in place to protect member data privacy? Detail strict data governance protocols, such as data minimization, access controls, and encryption standards, to maintain member trust.
3. Operational Readiness and Governance
- Do you have the necessary expertise and infrastructure to implement AI responsibly? Take stock of your current capabilities and identify areas where you may need to invest in talent, training, or technology to execute your AI policy effectively.
- How will you measure the success and ROI of your AI initiatives? Define clear metrics tied to your strategic goals and establish a framework for regularly monitoring and reporting on the performance of your AI systems.
By answering these questions, you'll be well on your way to developing a comprehensive and robust AI policy. Have questions? Reach out to us at info@helloaviary.ai
GENERATIVE AI WORD OF THE DAY
Compute
In the context of AI, "compute" refers to the processing power and resources needed to run artificial intelligence algorithms and models. It's like the brain power of a computer system, determining how quickly and efficiently it can perform complex calculations and tasks. More compute allows AI systems to handle larger amounts of data, run more sophisticated algorithms, and produce results faster. Just as a more powerful engine lets a car go faster, more compute enables AI to tackle more challenging problems and deliver better performance.
GENERATIVE AI IN FINANCE
The latest news at the intersection of GenAI and Finance
Business Leaders Doubling AI Budgets in 2025, EY Survey
EY's recent AI Pulse Survey reveals that business leaders across various industries, including financial services, are planning to significantly increase their AI investments. The survey found that 95% of respondents are currently investing in AI, with many planning to at least double their investment by 2025. Companies are seeing positive impacts from AI, including improvements in operational efficiencies, employee productivity, and customer satisfaction.
However, the survey also highlighted some concerns. Many organizations lack proper governance for AI implementation, with only 36% investing in data infrastructure and just over half planning to increase ethical AI use. Additionally, businesses are struggling to find employees with AI skill sets, despite prioritizing AI knowledge in new hires.
So what:
As competitors ramp up AI investments, credit unions risk falling behind if they don't act strategically. However, the survey's findings on governance and ethics underscore the importance of responsible AI adoption. CU leaders who prioritize developing robust data infrastructure and ethical AI frameworks will not only mitigate risks but also align with credit unions' member-centric values, potentially creating a competitive advantage in trustworthy AI implementation.
About AviaryAI
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