Another Crazy Day in AI 2/105

Another Crazy Day in AI: The Enduring Power of the Spreadsheet

Dec 5
4 min read

Hello, AI Enthusiasts.

Hope your week’s on track. In the world of AI, things are anything but slow.

A recent podcast looks at why Excel—a 40-year-old program—refuses to die, from personal hacks to competitive tournaments, and what it means for organizations struggling to move on... even in the age of AI.

Cybersecurity is racing to keep up too. CEO of Palo Alto Networks argued that the biggest AI cybersecurity risks aren’t just about protection, they’re about detecting and fixing problems fast. Prevention alone won’t cut it.

Meanwhile, Elon Musk weighs in on AI safety, stressing that truth and curiosity are vital to avoid hallucinations and chaos. Of course, even brilliant systems aren’t immune to bad data.

Here's another crazy day in AI:

Why Microsoft Excel still dominates after 40 years
A CEO says AI threats require a new detection strategy
Elon Musk lists what AI needs to avoid danger
Some AI tools to try out

TODAY'S FEATURED ITEM: Excel at 40 and Still Dominant

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)

Can a 40-year-old spreadsheet program really compete in the age of artificial intelligence and cloud computing?

A recent episode of The Big Take from Bloomberg Podcasts, hosted by Sarah Holder and featuring Bloomberg's Dina Bass and Businessweek's Max Chafkin, takes a closer look at Microsoft Excel's place in modern business and culture. The conversation explores how a program that's been around for four decades continues to dominate workplaces across the globe. They cover everything from the surprisingly competitive world of Excel championships to the personal spreadsheets that former Microsoft CEO Steve Ballmer uses to track his daily life. More importantly, they discuss the challenges Excel faces today and why organizations find it so difficult to move away from it.

What the episode walks through:

The growing interest in Excel competitions and how they highlight the skill involved in advanced spreadsheet work.
The ways Excel has become tightly integrated into daily operations for businesses, nonprofits, and government offices over the years.
A look back at the earliest spreadsheet tools, starting with VisiCalc and eventually leading to Excel’s broader adoption.
How Microsoft’s bundling of Excel with the broader Office suite helped establish it as a workplace standard.
The popularity of Google Sheets in schools and how different workplace expectations shape which tools employees end up using.
Newer software that supports data analysis but still leans on spreadsheets as the underlying structure.
Why many people continue to find the spreadsheet layout clear, practical, and easy to navigate.

The episode brings up some good questions about why organizational change tends to lag behind technological possibilities. Moving from Excel to something else involves retraining employees, reworking established processes, updating systems that connect to it, and keeping compatibility with others who still use it. Those obstacles are real and help explain why many companies haven't switched even when free alternatives exist. That said, some businesses have moved to other tools successfully, particularly when their priorities lean toward collaboration or cloud functionality rather than maintaining legacy workflows.

What stands out in the discussion is how the spreadsheet format itself keeps coming up. People have organized data in rows and columns for a really long time, well before computers. Whether that's because the format genuinely matches how we think about numerical information, or just because we're used to it, is hard to say. The conversation digs into why a 40-year-old program has managed to stick around despite newer competition, looking at everything from the practical headaches of switching to questions about whether spreadsheets align with how our minds work. It's a reminder that having better technology available doesn't automatically mean people will adopt it.

Watch on YouTube here.

Listen on Apple Podcasts here.

Listen on Spotify here.

OTHER INTERESTING AI HIGHLIGHTS:

A CEO Says AI Threats Require A New Detection Strategy

/Josephine Walker, Breaking News and General Assignment Reporter, on Axios

At Axios’ AI+ Summit, Palo Alto Networks CEO Nikesh Arora warned that rapidly evolving AI threats demand a shift in cybersecurity priorities. Instead of pouring resources solely into protection, he argues the industry must emphasize detection and remediation—areas where AI can make the biggest impact. Arora pointed to rising automated attacks and lagging U.S. cyber investments as signs that organizations need to rethink their defenses. His comments come as Palo Alto makes major acquisitions and expands its footprint in identity and AI-driven security.

Another Crazy Day in AI: Human Rights, Machine Speech, and Everything Between

Dec 1
4 min read

Hello, AI Enthusiasts.

Back at your desk and catching up?

A recent podcast brought together an esteemed economist and a nation’s leading legal scholar for a conversation about liberal democracies, AI, and the blurry line between human and machine. They touch on everything from everyday policies to the challenges of updating frameworks for rights and freedoms in a world of machine-assisted creation.

Meanwhile, the FDA is going big on AI for internal workflows... rolling out agentic tools to all staff. And if you think small can’t compete with big, Runway just proved otherwise with its new video-generation model. New month, same chaos, more AI.

Here's another crazy day in AI:

Cass Sunstein on liberalism, rights, and machine speech
FDA launches agency-wide agentic AI platform
Runway’s new video model outperforms top tech rivals
Some AI tools to try out

TODAY'S FEATURED ITEM: Rights, Technology, and Where They Intersect

Image Credit: Wowza (created with Ideogram)

What if the biggest threat to modern liberalism isn't its ideas, but the forces pushing against it, including the technologies we're building?

In a recent episode of Conversations with Tyler podcast, economist Tyler Cowen sits down with Cass Sunstein at Harvard Law School for a wide-ranging conversation that touches on some of the most pressing questions facing liberal democracies today. Sunstein, who remains one of the most frequently cited legal scholars in the world, has an unusual claim to fame this year: five books published in a single year. Among them are works examining liberalism, the capabilities and limitations of artificial intelligence, and the growing concern around manipulation in both commercial and political spheres. Their discussion moves fluidly between immigration enforcement, the constitutional status of AI-generated speech, and whether our current frameworks for rights and freedoms can adapt to a world where the line between human and machine contribution grows increasingly blurred.

Here's what came up in the conversation:

Liberalism faces pressures that stem from long-standing human tendencies toward fear, order, and certainty.
Immigration remains a complicated area where humane treatment, legal boundaries, and effective enforcement meet.
Many current contributors to liberal thought come from economics and behavioral science rather than traditional philosophy.
Certain strands of modern activism draw on classic liberal critiques but sometimes test norms of open disagreement.
AI does not hold individual rights, though AI-generated content raises questions around responsibility and constitutional interpretation.
Sunstein suggests considering a legal right not to be manipulated as influence becomes more targeted and data driven.
The role of AI in future judicial processes brings up questions about fairness, trust, and the value of human judgment.

There's something refreshing about listening to two people think through hard problems without pretending they have everything figured out. Sunstein tells a story from his time at the Department of Homeland Security, when he visited the southern border and briefly spoke with two Russian men waiting in line. Just asking them if they were okay—that simple human acknowledgment—stuck with him as a reminder that policy debates always involve real people in specific situations. The conversation about AI and constitutional rights has a similar quality. Nobody's claiming to know exactly where the lines should be drawn. A toaster that says "toast is ready" obviously doesn't need First Amendment protection, but what happens when AI and human contribution become so intertwined that separating them gets messy? These remain open questions.

The discussion keeps returning to something important: liberal societies need more than just well-designed institutions and clear laws. They depend on people actually practicing cooperation, assuming good faith in others, and maintaining respect across disagreements. Those habits prove surprisingly fragile under pressure. Cowen asks pointed questions throughout—whether immigration enforcement can avoid brutality, whether libel law can still function, whether we can meaningfully distinguish manipulation from ordinary persuasion. Sunstein responds honestly, sometimes suggesting new approaches, sometimes acknowledging we're still working through the implications. For anyone trying to understand the challenges facing liberal democracies right now, this conversation offers a grounded look at where the real complications lie and why even experts are still figuring things out.

Check it out here.

Listen on Spotify here.

Watch on YouTube here.

Listen on Apple Podcasts here.

OTHER INTERESTING AI HIGHLIGHTS:

FDA Launches Agency-Wide Agentic AI Platform

/FDA News Release

The FDA has officially rolled out agentic AI tools to all agency employees, giving teams the ability to build more complex, multi-step workflows that support tasks across reviews, inspections, compliance, and administration. The rollout builds on the success of Elsa, the agency’s earlier LLM tool, which more than 70 percent of staff adopted voluntarily. This new system emphasizes human oversight, strong security controls, and strict protection of sensitive data, especially since no input is used for model training. The agency is also launching a two-month internal challenge to encourage staff to build practical AI solutions ahead of FDA Scientific Computing Day in early 2026.

Another Crazy Day in AI: Can Better Data Actually Help Students Succeed?

Nov 28
4 min read

Updated: Dec 1

Hello, AI Enthusiasts.

Hope your Thanksgiving went well — whether you spent it cooking, traveling, or defending your favorite side dish. If you’re easing back into things (or still working through leftovers), here’s a little weekend food for thought.

A recent podcast explored CampusLens, a tool that shows how predictive AI can help advisers support students without magic or guesswork. It’s all about spotting patterns early so students get the guidance they actually need.

And if you’re staring at a fridge full of leftovers, A writer from CNET shared how ChatGPT can turn them into creative meals in minutes, no recipe panic required!

Meanwhile, Amazon’s Alexa Plus is stepping up its game, learning to have more natural, context-aware conversations so your smart speaker might finally feel… smart.

Take a break and savor the weekend.

Here's another crazy day in AI:

How colleges use data to help learners
AI joins the holiday shopping frenzy
What to know about Amazon’s Alexa+ upgrade
Some AI tools to try out

TODAY'S FEATURED ITEM: Inside a College's Decision on Analytics Tools

Image Credit: Wowza (created with Ideogram)

What if the biggest obstacle to helping students succeed isn't a lack of data, but having too much of it scattered across systems that don't talk to each other?

In a recent episode of Voices of Student Success, Inside Higher Ed reporter and host Ashley Mowreader talks with Tracy Hartzler, president of Central New Mexico Community College, about the school's decision to adopt CampusLens, a predictive data tool designed to help advisers and faculty better understand student patterns and program outcomes. Their conversation looks at how community colleges manage large amounts of data, the pressures of serving diverse learners, and the practical realities of bringing new tools into long-standing systems.

The conversation touches on:

CNM currently uses seven legacy systems and over 100 applications just to generate reports, which creates delays when staff need information to help students
The college is exploring whether predictive analytics can flag students who might benefit from early intervention
Career Lens tracks wage outcomes for graduates and helps determine which programs meet Workforce Pell eligibility requirements
Hartzler weighs the costs of adding features to multiple existing systems versus implementing one comprehensive tool
Teams across the institution spent five to six months evaluating the decision before moving forward
The college created a pilot fund where staff can propose three-month projects to test different uses of the technology
CNM's governing board asks whether technology investments actually improve outcomes for students and the community

Hartzler is straightforward about what this process actually looks like on the ground. She mentions the financial commitment involved, the training that staff will need, and how easy it is to just move old workflows onto new platforms without really changing anything. There's also the fact that people who've developed expertise around existing systems might worry about where they fit when everything changes. Her team took months to evaluate this decision, which suggests they understand the stakes. What stands out is how she frames the core problem: advisers checking multiple systems to get basic information about one student, faculty manually pulling together data that could inform their teaching, and everyone spending time on administrative tasks instead of actually working with students.

The episode gets at something many colleges are dealing with right now. Having data and being able to use it effectively are two different things. Hartzler points out that staying with systems that exhaust staff and leave students without timely support has its own set of consequences. Whether predictive analytics tools end up being helpful will likely vary depending on each institution's infrastructure, resources, and willingness to reconsider how things have always been done. But the questions about making information accessible to the people who need it, and doing so in ways that don't add to everyone's workload, are ones that a lot of campuses are asking themselves.

Read the full article here.

Listen on Spotify here.

Watch on YouTube here.

Listen on Apple Podcasts here.

OTHER INTERESTING AI HIGHLIGHTS:

AI Shows How to Repurpose Your Holiday Leftovers

/Amanda Smith, Freelance Journalist and Writer, Contributor, on CNET

If your fridge is overflowing with Thanksgiving leftovers, AI can help turn the chaos into new meals. CNET’s Amanda Smith walks through how ChatGPT can suggest recipes based on whatever ingredients you list—whether that’s takeout extras, pantry stragglers, or half-used produce. By prompting the chatbot with preferences, substitutions, and dietary needs, users can refine dishes until they land on something they actually want to make. It’s a simple way to reduce waste, spark creativity, and get more mileage out of the holiday feast.