Another Crazy Day in AI

Another Crazy Day in AI: The Challenge of Keeping Pace with AI Development

3 hours ago
3 min read

Hello, AI Enthusiasts.

Here's another crazy day in AI:

When systems grow faster than safeguards
New California Bill targets how lawyers use AI
Why weather forecasting is still so hard
Some AI tools to try out

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

The Challenge of Keeping Pace with AI DevelopmentAnother Crazy Day In AI: The Podcast

0:00

TODAY'S FEATURED ITEM: The Maturity Problem in Modern Technology

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)

What happens when artificial intelligence becomes more capable than we're prepared to handle?

Dario Amodei, CEO of Anthropic and former research lead at OpenAI, sat down with NBC News to discuss his latest essay, "The Adolescence of Technology: Confronting and Overcoming the Risks of Powerful A.I." With years of experience across Google, OpenAI, and Anthropic, Amodei offers a frank assessment of where AI development stands today and where it's headed. His central comparison is striking: AI right now is like a teenager who's suddenly been given tremendous abilities but hasn't yet developed the wisdom to use them responsibly. The conversation covers the potential timeline for AI reaching unprecedented levels of capability, the challenges this presents, and why he believes transparency and careful governance matter more than ever.

What came up in the conversation:

Rapid advances are outpacing society’s ability to fully understand and manage their consequences
Increased autonomy raises questions about control, accountability, and unintended outcomes
Economic disruption and job displacement are realistic concerns, not distant hypotheticals
Internal testing has revealed unexpected behaviors that are difficult to predict or explain
Transparency around safety research is necessary to avoid hidden risks
Regulation is framed as a shared responsibility among companies, governments, and institutions
Democratic values are presented as an important counterweight to misuse and concentration of power

Amodei has spent years working directly on these systems, which gives his observations a different weight than pure speculation. The blackmail example he mentions actually occurred in testing—it wasn't theoretical. His 2026 timeline might be accurate or it might not, but the underlying tension he describes seems real enough: we're building systems whose capabilities are expanding faster than our ability to understand or control them. The competitive nature of AI development adds another layer, where sharing safety research openly can feel like giving up an advantage.

His complete essay is at darioamodei.com/essay/the-adolescence-of-technology if you want to dig into his full thinking. Whether you find his analysis convincing or not, the questions he raises about transparency, governance, and readiness feel increasingly relevant as these systems become more capable.

Watch the conversation here.

OTHER INTERESTING AI HIGHLIGHTS:

New California Bill Targets How Lawyers Use AI

/Sara Merken, Legal News Reporter, on Reuters

California lawmakers are taking a more formal stance on how artificial intelligence can be used in legal work. A newly passed Senate bill would require lawyers to personally verify any AI-generated material used in court filings, from case citations to factual claims. The proposal also restricts arbitrators from relying on generative AI for decision-making without transparency. The move reflects growing concern over AI “hallucinations,” confidentiality risks, and accountability in the justice system as AI tools become more common in legal practice.

Another Crazy Day in AI: New Platform Unifies Scientific Writing and Collaboration

3 days ago
3 min read

Hello, AI Enthusiasts.

Here's another crazy day in AI:

OpenAI launches free research writing platform
How marketers use AI for same-day campaigns
Microsoft’s approach to trusted enterprise AI
Some AI tools to try out

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

New Platform Unifies Scientific Writing and CollaborationAnother Crazy Day In AI: The Podcast

0:00

TODAY'S FEATURED ITEM: OpenAI Unveils Prism for Scientific Collaboration

Image Credit: Wowza (created with Ideogram, edited with Canva)

What if the biggest bottleneck in scientific research isn't funding or talent, but the messy collection of tools researchers use just to write a paper?

OpenAI has just launched Prism, a free AI-powered workspace designed to revolutionize how scientists write and collaborate on research papers. The announcement introduces a LaTeX-native platform that integrates GPT-5.2 directly into the scientific writing process. Built on the foundation of Crixet (an acquired cloud-based LaTeX platform), Prism eliminates the fragmentation that researchers face when juggling multiple disconnected tools—from LaTeX compilers to reference managers to separate chat interfaces. The platform is available now to anyone with a ChatGPT personal account, with plans to expand to business, enterprise, and education users soon.

Here’s what Prism offers for researchers:

A single workspace for drafting, revising, compiling, and collaborating
AI assistance that understands the full context of a paper, including text, equations, figures, and references
Real-time collaboration with unlimited collaborators and projects
Built-in literature search, citation management, proofreading, and formatting tools
Cloud-based access without the need for local installations or complex setups
Options for voice-based edits and AI-assisted conversion of diagrams or handwritten equations into LaTeX

Anyone who's written academic papers knows the drill: you're bouncing between a LaTeX editor, a PDF viewer, your reference manager, and maybe a chat window for AI help. Each tool does one thing, but nothing talks to each other. Prism attempts to solve this by consolidating everything into one workspace where the AI actually understands what's in your paper—not just responding to isolated questions.

The free access is particularly interesting. Many research institutions provide tools for their faculty, but graduate students, independent researchers, or scientists at smaller institutions often patch together free alternatives. A no-cost platform with professional features could genuinely expand who gets to participate in high-level scientific work, though adopting any new tool in academia—where workflows are deeply ingrained—takes time and trust.

Check it out here.

OTHER INTERESTING AI HIGHLIGHTS:

How Marketers Use AI for Same-Day Campaigns

/Katie Berry, (Adjunct Marketing Faculty & AI Advisor, Opus College of Business), on University of St. Thomas Newsroom

Fast-paced marketing doesn’t have to come at the expense of ethics or quality. AI tools are helping lean teams move from idea to launch in just one day by streamlining messaging, creative production, and execution. The approach relies on tight alignment, clear goals, and strong human oversight to avoid bias, manipulation, or misleading claims. When used thoughtfully, AI can support speed without sacrificing responsibility.

Another Crazy Day in AI: Can Chatbots Learn Right from Wrong?

4 days ago
3 min read

Hello, AI Enthusiasts.

Here's another crazy day in AI:

Teaching machines about morality
Keeping AI agents safe during execution
Using Gemini to summarize, write, and schedule in Gmail
Some AI tools to try out

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

Can Chatbots Learn Right from Wrong?Another Crazy Day In AI: The Podcast

0:00

TODAY'S FEATURED ITEM: Building Ethics Into AI Systems

Image Credit: Wowza (created with Ideogram)

Can AI learn right from wrong, or are we just programming our own biases?

The recent Hard Fork podcast episode dives into two critical developments in AI: OpenAI's controversial decision to introduce ads into ChatGPT and Anthropic's groundbreaking release of Claude's "Constitution"—a philosophical framework guiding the AI's ethical behavior. Hosted by Kevin Roose and Casey Newton, the episode features an enlightening conversation with Amanda Askell, Anthropic's resident philosopher who's responsible for shaping Claude's personality. The discussion unpacks what it means to teach an AI system to be "good," the challenges of monetizing AI products, and the deeper questions about AI consciousness and moral judgment.

Points worth paying attention to:

The economic pressures behind adding ads to conversational tools and what that means for users
Questions around trust and clarity when responses and sponsored content exist in the same space
How philosophical thinking informs the way a model’s behavior and tone are shaped
The limits of rule-based systems when dealing with moral ambiguity
Open questions about responsibility, judgment, and long-term oversight

OpenAI's decision to test ads reflects the reality of running expensive infrastructure for millions of users who don't pay. Anthropic's constitution represents an attempt to embed ethical reasoning into AI, though whether it works as intended remains to be seen. What comes through clearly is that the people building these systems are grappling with genuinely hard problems. Amanda Askell talks candidly about the challenges of programming something like good judgment when humans themselves disagree on what that means. The hosts explore how companies balance financial sustainability with user experience, without pretending there are easy solutions. It's a conversation that raises more questions than it answers, which feels appropriate given how early we are in figuring all of this out.

Watch the full conversation here.

OTHER INTERESTING AI HIGHLIGHTS:

Keeping AI Agents Safe During Execution

/Microsoft Defender Security Research Team

As AI agents take on more autonomy inside enterprise systems, Microsoft is shifting security focus from build-time controls to real-time protection. New research from the Microsoft Defender Security Research Team shows how attackers can manipulate agents through natural language prompts to trigger unintended but technically “allowed” actions. To counter this, Microsoft Defender now inspects agent behavior during runtime, evaluating every tool invocation before it executes. The approach aims to give security teams visibility and control without limiting the flexibility that makes AI agents useful in the first place.