Another Crazy Day in AI 2/109

Another Crazy Day in AI: Will Education Systems Survive the Age of Intelligent Machines?

Jan 22
3 min read

Hello, AI Enthusiasts.

Here's another crazy day in AI:

What we know and don't know about school technology
Amazon rolls out a health chatbot for One Medical users
Google adds Personal Intelligence to AI Search
Some AI tools to try out

🎧 Listen to a quick breakdown of today’s stories.

Will Education Systems Survive the Age of Intelligent Machines?Another Crazy Day In AI: The Podcast

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TODAY'S FEATURED ITEM: Can AI Save Education or Destroy It?

A robotic scientist in a classic white coat with 'AI Scientist' on its back stands beside a human scientist with 'Human Scientist' on their coat, looking towards the AI Scientist.

Image Credit: Wowza (created with Ideogram)

How should education systems respond when technology changes faster than curriculums can keep up?

The recent episode of CNBC's "The Tech Download" podcast features a conversation between hosts Arjun Kharpal and Steve Kovach and Lila Ibrahim, Chief Operating Officer of Google DeepMind. Their discussion examines how artificial intelligence is beginning to appear in classrooms, what early results show, and the questions this raises for teachers, students, and institutions. Ibrahim brings both her professional perspective from DeepMind and personal experiences as a mother watching her daughters navigate learning in different ways.

Points raised during the discussion:

Learning is being examined through research and classroom experience, not only technical development
Early pilots suggest some teachers are gaining time for planning and student interaction
Reducing administrative demands may help ease teacher workload, depending on context
Clear guidance is needed to support responsible classroom use
Personalized approaches may benefit students who struggle with traditional learning formats
Ethical input from educators and social scientists informs development decisions
Education planning is closely connected to how students prepare for future work

Schools are trying to figure out what to do with AI tools that students are already using, sometimes openly and sometimes not. Some institutions are testing them carefully, others are prohibiting them entirely, and many are working through policies without clear roadmaps. The Northern Ireland pilot offers one data point—teachers getting hours back in their weeks matters when burnout is high. But taking something from a controlled pilot to widespread implementation means dealing with budget constraints, varying comfort levels with technology, and the fact that not all schools start from the same place in terms of resources or infrastructure.

Ibrahim's perspective is one voice in a much larger conversation happening across education right now. Her background spans technology access work, executive leadership at an AI company, and raising daughters who learn in different ways. The questions she raises don't have settled answers yet. Whether AI tools genuinely improve learning outcomes, how to teach responsible use, what happens to students without equal access, how teachers should be trained—these are all being worked out as the technology continues developing. The decisions being made now by schools, tech companies, and policymakers will matter for years to come, and most people involved are honest about still learning as they go.

Watch the full conversation here.

OTHER INTERESTING AI HIGHLIGHTS:

Amazon Rolls Out a Health Chatbot for One Medical Users

/Emily Olsen, (Reporter), on MedTech Div

Amazon has launched a health-focused AI chatbot inside the One Medical app, giving members a new way to ask health questions, assess symptoms, and manage care. The assistant can reference a patient’s existing medical records to offer guidance, help book appointments, renew prescriptions, or decide between virtual and in-person care. Amazon says the tool includes safety guardrails that escalate cases to clinicians when medical judgment is required. The move comes as major AI companies push deeper into healthcare, even as concerns around accuracy, hallucinations, and patient safety continue to grow.

Another Crazy Day in AI: Why This Technology Cycle Is Different

Jan 22
3 min read

Hello, AI Enthusiasts.

Here's another crazy day in AI:

Beyond the bubble conversation
How AI shopping protocols are taking shape
Why critical thinking matters more in an AI era
Some AI tools to try out

🎧 Listen to a quick breakdown of today’s stories.

Why This Technology Cycle Is DifferentAnother Crazy Day In AI: The Podcast

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TODAY'S FEATURED ITEM: Where AI Stands and Where It's Going

Image Credit: Wowza (created with Ideogram)

How can we tell whether momentum is sustainable or simply loud?

What if everything we've seen from artificial intelligence so far—the millions using ChatGPT, the productivity gains, the heated debates about bubbles—is just the warm-up? In a recent OpenAI Podcast episode, CFO Sarah Friar sits down with legendary investor Vinod Khosla to argue that we're not in an AI bubble, but rather at the very start of a fundamental infrastructure shift as transformative as electricity itself. The conversation unpacks why the real story of 2026 isn't whether AI will matter, but how quickly we can close the gap between AI's potential and how people actually use it today.

The discussion moves beyond market speculation to explore what's actually happening on the ground. Friar and Khosla examine practical applications across consumer and enterprise sectors, the metrics that matter when measuring genuine demand, and what the next few years might bring for healthcare, robotics, and workplace productivity. Their central premise is straightforward: the best indicator of real adoption isn't stock prices or venture capital flows, but how much people and businesses actually use these tools.

Key points from their conversation include:

Practical adoption is what counts: Real impact comes from people and organizations actually using AI tools consistently.
Foundational infrastructure: AI is becoming embedded in systems and processes, influencing how work and services are delivered.
Cross-industry possibilities: Healthcare, robotics, and workplace productivity are already showing measurable benefits.
Engagement over hype: Metrics that matter focus on real-world usage, not media attention or investment levels.
Untapped potential remains: While adoption is growing, much of AI’s capabilities are still waiting to be realized.

The episode walks a line between describing what's already happening and predicting what might come next. When Friar talks about finance teams using AI to scan contracts or Khosla mentions companies running lean operations, these reflect current reality in some organizations. The physician adoption numbers are concrete. At the same time, both speakers have professional interests in presenting AI growth favorably—one runs finance at OpenAI, the other is a major investor. Their point about tracking API calls rather than stock prices to understand demand makes sense on its face, though we're still early enough that it's unclear which metrics will prove most telling. The bolder predictions about robotics and economic changes depend on variables that are hard to forecast with confidence. What comes through most clearly is that some organizations are finding genuine value in AI tools today, regulatory frameworks are still catching up in areas like healthcare, and there's a significant gap between what these systems can theoretically do and how most people currently use them.

Watch the full conversation here.

OTHER INTERESTING AI HIGHLIGHTS:

How AI Shopping Protocols Are Taking Shape

/PayPal Newsroom

AI-powered shopping is moving fast, with assistants like ChatGPT and Gemini increasingly handling product discovery, comparisons, and even purchases. To make this possible, new agentic commerce protocols—such as OpenAI’s ACP and Google’s UCP—are emerging to define how AI agents, merchants, and payment systems interact. PayPal breaks down how these protocols differ and why trust, identity, payments, and fraud protection become even more critical when an AI agent clicks “Buy.” For merchants, understanding this evolving protocol landscape is quickly becoming a prerequisite for participating in AI-driven commerce.

Another Crazy Day in AI: Democratizing Access or Deepening Divides?

Jan 20
3 min read

Hello, AI Enthusiasts.

Here's another crazy day in AI:

AI as the new economic foundation
HR leaders say AI is a people story
Meta’s vision for everyday superintelligence
Some AI tools to try out

🎧 Listen to a quick breakdown of today’s stories.

Democratizing Access or Deepening Divides?Another Crazy Day In AI: The Podcast

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TODAY'S FEATURED ITEM: The New Engine of Economic Growth

Image Credit: Wowza (created with Ideogram)

Can AI truly deliver on its promise to democratize opportunity globally, or will it deepen the divide between the skilled and the marginalized?

At the World Economic Forum in Davos, Microsoft CEO Satya Nadella joined BlackRock CEO and WEF Interim Co-Chair Larry Fink for a live conversation on how productivity gains emerge across economies and organizations. Covered by DRM News, the discussion focused on the real-world conditions that influence whether new tools translate into broad economic value.

The exchange looked at practical factors shaping adoption, including infrastructure, investment, workforce readiness, and organizational design. It also acknowledged uneven progress across regions, noting how access, education, and policy environments affect who benefits and who may be left behind.

Here are some of the points that came through in the conversation:

Technology alone does not guarantee productivity gains; support systems like skilled labor, organizational design, and infrastructure are critical.
Preparing employees with training and upskilling increases the likelihood that tools will be used effectively.
Differences in access, policy, and education mean that adoption and benefits are uneven across regions and industries.
Collaboration among governments, businesses, and educational institutions can help expand opportunities and reduce inequities.

Nadella and Fink discussed what needs to happen for the technology to create value beyond major tech companies and developed economies—things like better power grids, capital investment, and workforce training. But they also acknowledged that none of these prerequisites are guaranteed to materialize evenly across the world. Fink raised concerns about whether current applications mainly benefit educated populations and developed markets, potentially widening existing gaps. Nadella pointed to examples like the Indian farmer as evidence of broader reach, but neither presenter suggested the outcome is predetermined.

What becomes clear is that the technology itself has moved past the experimental stage, but everything else around it remains unsettled. A professional in New York and a farmer in rural India might both have access to AI tools, but whether they get similar practical benefits depends on infrastructure quality, internet connectivity, training availability, local language support, and regulatory environments. These aren't problems that engineers or developers can solve on their own. They require coordination between private investment and public policy, and they play out differently in every country and region. How institutions and governments respond to these challenges over the coming years will likely matter more than any individual technical breakthrough in determining who actually benefits from AI and who gets left watching from the sidelines.

Watch the full conversation here.

OTHER INTERESTING AI HIGHLIGHTS:

HR Leaders Say AI Is a People Story

/Adam DeRose, (Senior Reporter), on HR Brew

HR leaders argue that the AI transformation isn’t just about new tools—it’s fundamentally about people. Speaking at CES, executives from Salesforce, GitLab, and Samsung emphasized that while AI fluency matters, human skills like curiosity, judgment, creativity, and adaptability will matter even more. AI is framed not as a replacement, but as an amplifier of human intelligence, reshaping how work gets done and how workers are supported. The takeaway: companies that leave HR out of AI strategy risk having to rebuild later.