Signal + Noise: GEN AI WEEKLY RUN DOWN, 1.22.25
By Isaiah Steinfeld, Founder & CEO, Neue Alchemy
January 22, 2025
Welcome back to the GEN AI Weekly Run Down — Generative AI is everywhere, but its story is far from fully written. It’s the sharp edge of transformation, carving out opportunities and rewriting how industries think, work, and create. This newsletter is here to explore that evolution—informing, sparking ideas, and (hopefully) starting some meaningful conversations along the way.
Buckle up; this one’s a longer read, but packed with insights you won’t want to miss.
Let’s get into it.
🚀 Stargate Project: $500 Billion AI Infrastructure Initiative
The Stargate Project is poised to redefine AI infrastructure in the U.S. With $500 billion in planned investments, it’s a collaboration between OpenAI, SoftBank, Oracle, Microsoft, NVIDIA, and Arm.
What’s New: The first data center is already under construction in Abilene, Texas, with plans to build campuses across the country.
Why It Matters: This project addresses critical compute shortages and solidifies the U.S.’s leadership in AI, with ripple effects likely to impact global innovation and competition. It also raises the stakes for international AI players, potentially reshaping cross-border collaborations and market dynamics, while creating hundreds of thousands of U.S.-based jobs.
Hot Take: Stargate could redefine the rules of AI innovation. While the scale is impressive, it also raises questions about who benefits most—startups, enterprises, or governments?
What to Consider: How can smaller organizations leverage infrastructure like Stargate without being left behind?
📉 Gen AI ROI Falls Short of Expectations, But Belief Persists
Deloitte’s latest survey reveals that while ROI on generative AI hasn’t materialized as quickly as expected, enthusiasm remains high.
Why It Matters: This finding underscores the importance of defining clear metrics and addressing deployment barriers.
Hot Take: Generative AI isn’t about quick wins—it’s about long-term transformation. To succeed, companies need to move beyond the hype and adopt a strategic approach. It’s a “Yes, And” moment: embrace pilots, but focus on where you’re headed. Generative AI is not a technology looking for a problem—it’s a paradigm shift. If you’re not testing and building, you risk falling behind.
What to Consider: What’s your biggest barrier to scaling AI, and how are you addressing it?
🌍 Google.org Launches $30M Generative AI Accelerator
Google.org Invests $30M in Generative AI for Good
Google.org is channeling $30 million into a generative AI accelerator to empower nonprofits tackling challenges in healthcare, education, and climate action. Selected organizations will gain access to funding, technical expertise, and AI tools to help scale their impact and solve critical societal problems.
Why It Matters: This isn’t just about technology—it’s about using AI to address the issues that matter most to humanity. From improving access to healthcare in underserved regions to creating tools that support education equity, these investments demonstrate the vast potential of AI beyond commercial gains. It’s a signal to the industry that purpose-driven innovation can coexist with groundbreaking technology.
Hot Take: Funding tied to purpose-driven impact is where AI truly shines, but the accelerator’s success will ultimately depend on how well these nonprofits can translate AI capabilities into real-world outcomes. Execution is key: it’s not just about deploying AI but ensuring it’s solving the right problems in sustainable ways. If done right, this could set a new standard for the role of AI in social innovation -- Personally I want to see more of this.
What to Consider: What problems in your community or industry could benefit from AI solutions? How might you collaborate with partners or align with initiatives like this to drive meaningful change? These are the types of questions leaders and organizations should be asking to harness AI for the greater good.
💼 Mistral AI Plans IPO
French AI startup Mistral has announced plans for an initial public offering (IPO), aiming to raise significant capital to expand its open-weight AI model offerings.
Why It Matters: Mistral’s move signals growing confidence in the market for open-weight AI models, positioning the company to challenge incumbents like OpenAI and Anthropic.
Hot Take: Mistral’s decision to go public is bold and refreshing. It reflects a belief in transparency and democratization—not just in their open-weight models but in how they’re choosing to grow. It’s a confident step that could inspire other startups to rethink traditional fundraising.
What to Consider: Could this IPO pave the way for a wave of AI startups to go public, or will it highlight the risks of entering public markets too early in a still-evolving industry?
📊 Gen AI in 2025: "Playtime is over, time to get practical"...
NTT DATA reports that 90% of executives are moving from experimentation to ROI-driven AI projects, leaving behind pilot fatigue.
Why It Matters: This signals a shift toward practical, outcome-focused AI investments.
Hot Take: “AI experimentation is out; execution is in” feels too narrow. It’s not an either-or—it’s “yes, and.” The best companies are those that execute with precision while making experimentation a core competency. Great experimentation isn’t random; it’s structured, strategic, and always aimed at solving real problems. If you’re wondering how to bridge that gap, this is my bread and butter—let’s connect, and I’d be happy to help.
What to Consider: Are you ready to shift from exploration to implementation?
📜 Regulatory Shift: Trump Revokes Biden’s AI Executive Order
President Trump has rescinded a 2023 executive order by Joe Biden aimed at addressing AI risks and establishing ethical guardrails.
Why It Matters: This hands-off approach could accelerate innovation but may also lead to unchecked risks.
Hot Take: Regulations are a double-edged sword. Lack of oversight could spark growth—or chaos. The challenge is finding the balance.
What to Consider: How do we ensure ethical AI development in a minimally regulated environment?
💻 AI Vision Startup Metropolis Acquires Oosto for $125M
Metropolis, known for its AI-powered parking solutions, has acquired Oosto (formerly AnyVision) to expand its computer vision capabilities.
Why It Matters: By integrating Oosto’s tech, Metropolis aims to enhance its vehicle tracking and automated payment systems across 4,000 locations.
Hot Take: This acquisition highlights the growing role of computer vision in everyday applications. Keep an eye on how this scales beyond parking.
What to Consider: Where else could AI-powered vision disrupt traditional systems?
🧬 New Research: AI Systems Approach Human Cognition
A breakthrough study led by RIT researchers shows AI systems are nearing human-like information processing capabilities.
Why It Matters: Advances in AI cognition open new possibilities for NLP, robotics, and decision-making.
Hot Take: Human-like AI is exciting—and unsettling. Trust and transparency will be key as AI takes on more complex roles.
What to Consider: How does increasing AI complexity affect your trust in technology?
🎯 Microsoft: From Exclusivity to Collaboration
Microsoft’s once-exclusive partnership as OpenAI’s sole data center provider has shifted. The company now holds only a “right of first refusal” for OpenAI’s infrastructure needs, signaling more diverse collaborations in the future.
Why It Matters: This move reflects OpenAI’s ambition to scale its infrastructure beyond a single partner, opening doors for broader innovation.
Hot Take: Diversifying partnerships could make OpenAI more agile, but it’s also a wake-up call for Microsoft to stay competitive.
What to Consider: Could this pave the way for other cloud providers like AWS or Google to enter the fold?
🌟 Top Generative AI Trends for 2025
A new report outlines key trends in generative AI, including hyper-personalization, industry-specific AI, and regulatory challenges.
Why It Matters: These trends offer a roadmap for where innovation is heading and how industries are adapting.
Hot Take: Generative AI is becoming deeply embedded in industries. Adopting early isn’t enough—understanding the trends is critical.
What to Consider: Which trends align most with your goals, and how can you prepare for them now?
🔍 Perplexity’s API: Generative Search for All
AI-powered search engine Perplexity launched Sonar, an API that lets enterprises and developers integrate its generative AI tools into their applications.
Why It Matters: Generative search is becoming a competitive space, and APIs like this enable businesses to customize search experiences for specific use cases.
Hot Take: Perplexity’s move democratizes access to generative search, giving smaller developers a chance to compete in niche markets.
What to Consider: How might generative search tools like Sonar reshape customer experiences in industries like e-commerce or healthcare?
🧠 AWS Updates on AI for 2025
AWS announced several key updates to its AI offerings, including new tools for large-scale model training, integrations with generative AI, and healthcare-specific solutions.
Why It Matters: These updates underscore AWS’s commitment to remaining at the forefront of AI infrastructure and applications.
Hot Take: AWS is playing the long game in AI, choosing scalability and accessibility over quick wins. It’s still early days, and the real question isn’t who’s leading today—it’s who’s making the moves that will matter a decade from now.
What to Consider: How are you leveraging cloud-based AI tools to accelerate innovation?
⚔️ AI and Defense: Speeding the “Kill Chain”
The Department of Defense is leveraging AI to accelerate its decision-making process, particularly in identifying and assessing threats.
Why It Matters: AI’s role in national security is growing rapidly, offering significant advantages in defense capabilities.
Hot Take: While the efficiency gains are undeniable, the ethical implications of AI in defense warrant serious consideration.
What to Consider: As AI integrates into defense, where should the line be drawn between automation and human oversight?
📚 DeepSeek’s Open Model: A New Player in AI Benchmarks
Chinese AI lab DeepSeek released DeepSeek-R1, an open reasoning model that reportedly performs on par with OpenAI’s o1 on certain benchmarks.
Why It Matters: This raises the bar for open-source models, challenging proprietary leaders like OpenAI to keep innovating.
Hot Take: Open models like DeepSeek-R1 could democratize access to advanced AI capabilities, leveling the playing field globally.
What to Consider: How might open models reshape competition in the AI ecosystem?
Closing Thought: This week highlighted both the promise and complexity of generative AI—its ability to revolutionize industries and solve big problems, tempered by challenges like regulation, ethics, and achieving ROI. The key question isn’t just how we harness AI’s potential, but how we do so thoughtfully and strategically.
If you’re building, leading, creating, or just curious about where this all leads—let’s connect. Whether it’s an email, a virtual coffee chat, or an exchange of bold ideas, we’d love to hear your perspective. Together, we can chart a path through this ever-evolving landscape.
