I recently came across a striking story that perfectly captures a challenge many industries are grappling with today—how critical knowledge disappears when people retire or leave, and how rebuilding that expertise can take years. This isn’t just about factories and missiles—it’s happening right now in software engineering, and AI might be hiding the cracks until it’s too late.

When decades of know-how vanish overnight

At the 2023 Paris Air Show, Raytheon’s president shared how restarting production of the Stinger missile was a logistical nightmare. The original schematics were decades old, workers retired, and test equipment was gathering dust in warehouses. They had to bring back engineers in their 70s to teach younger workers how to build the missile by hand just like in the Carter era. Orders placed in 2022 for components wouldn’t arrive until 2026. The Pentagon hadn’t bought a new Stinger in twenty years, so the production line had essentially shut down from a lack of institutional knowledge.

This story illustrates a broader pattern. When Russia invaded Ukraine, the U.S. and Europe had to scramble to supply weapons and ammunition. But years of optimization for cost-efficiency and peace-time economies had hollowed out manufacturing capacity. France hadn’t made propellant in seventeen years. Europe’s biggest TNT producer was just one plant in Poland. Key facilities were shut down or mothballed, leaving the continent unable to deliver promised supplies on time.

Lessons from Fogbank: Why written records aren’t enough

Perhaps the most striking example is the story of Fogbank, a classified nuclear warhead material produced from 1975 to 1989. When the government tried to recreate it in 2000, they found they simply couldn’t. Key experts who knew how to make it had retired or passed away, and official records missed an unintentional impurity critical to its function. Years and $69 million in reverse engineering later, they discovered the missing piece of “tribal knowledge” wasn’t documented anywhere.

This demonstrates a crucial insight—knowledge tied exclusively to people is fragile. No matter how digitized or documented a process might be, the tacit understanding that comes from years of hands-on experience often doesn’t survive without deliberate knowledge transfer.

What this means for software engineering and AI

I came across insights revealing that software engineering is following a similar trajectory, with worrying signs popping up. Just like defense manufacturing, building senior-level skill sets takes many years. Junior developers typically need 3-5 years to become competent mid-level engineers, and 5-8+ years to reach senior or architect roles. These timelines can’t simply be sped up by throwing money—or AI—at the problem.

Interestingly, a METR controlled trial found experienced developers using AI coding assistance actually took 19% longer to complete tasks than predicted, even though before starting they expected a 24% speed boost. Plus, AI-generated code now floods the workflow, making code review the new bottleneck, since humans still have to carefully vet what AI produces.

Hiring surveys reinforce this picture: many engineering leaders expect AI to reduce junior-level hiring, while computing programs see enrollment decline, meaning fewer fresh engineers entering the pipeline. When junior developers don’t go through the traditional process of debugging and learning from mistakes—and lean too heavily on AI—they risk developing what a DoD study calls “AI-mediated competence.” Essentially, they get good at prompting AI but not at understanding or critiquing its output.

This means when senior engineers retire or move on, their institutional knowledge isn’t replaced, and AI tools can’t fill those gaps—they only reflect the capabilities set by the humans who trained them. We might find ourselves in a future where entire layers of critical software expertise evaporate just as suddenly as Fogbank did in defense manufacturing.

Key takeaways for developers, teams, and leaders

• Don’t mistake AI as a shortcut for deep expertise. AI is a tool, not a replacement for experience and judgment.
• Prioritize deliberate knowledge transfer. Mentorship, documentation with context, and embedding ownership in junior engineers are crucial.
• Recognize that rebuilding lost skills takes years. It’s a long game that requires sustained investment beyond flashy innovation.

The defense industry’s decades-long struggle to restart production lines and recreate lost expertise teaches us an invaluable lesson: optimizing for short-term efficiency without nurturing the human pipeline can leave us vulnerable when crises hit. In software, as AI becomes more integrated, we can’t afford to lose sight of the fundamentals of building and retaining true technical mastery.

We’re already seeing the consequences—shrinking talent pools, reduced hands-on debugging experience, and an overreliance on AI-generated code. Only by recognizing the limits of AI as a crutch and recommitting to developing seasoned engineers can we avoid the costly mistakes of the past.

And if history teaches us anything it’s this: the bill always comes due.

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AI has taken center stage in global discussions like never before. I recently came across insights from the latest United Nations high-level meetings in New York, where world leaders addressed AI‘s enormous potential to both help and harm humanity. The growing concern is clear: AI is no longer just a tech issue—it’s a matter of international peace, security, and ethical responsibility.

Why the UN is stepping up on AI governance

During a recent UN Security Council session, Secretary-General Antonio Guterres pointed out that AI’s influence on peace and security is inevitable, but what really matters is how we shape its use responsibly. On the positive side, AI can anticipate crises like food insecurity, assist in de-mining efforts, and even detect early signs of violence outbreaks—potential game changers for prevention. Yet, without proper guardrails, AI risks being weaponized in ways that could escalate conflicts or spread misinformation.

Many world leaders, particularly from Europe, echoed this cautious optimism. Greek Prime Minister Kyriakos Mitsotakis urged the Council to rise to the AI challenge just as it once did with nuclear weapons—highlighting the need for governance that ensures militaries keep human oversight over AI-driven systems to avoid catastrophic mistakes. Meanwhile, Britain’s Deputy Prime Minister David Lammy pointed to AI’s ability to provide ultra-accurate real-time data analysis and early warnings that could, if harnessed properly, foster peace rather than conflict.

A new UN-led global AI forum and expert panel

Last month, the UN General Assembly made a major move by agreeing to create two new bodies focused on AI governance—a Scientific Panel of Experts and a Global Dialogue on AI Governance forum. Forty experts will be appointed to the panel, which will provide annual reports to inform international dialogue, starting with the first forum scheduled in Geneva in 2026.

This is being hailed by some experts as a landmark step toward inclusive global AI oversight. It’s perhaps the most globally inclusive approach so far, bringing all 193 UN member states into the conversation about AI’s future. Previous efforts like summits held by Britain, France, and South Korea have failed to produce binding safety pledges, making this UN initiative a potentially transformative platform.

However, there’s a note of skepticism from researchers who question whether the famously slow-moving UN bureaucracy can keep pace with rapidly evolving AI technology. Despite this, the commitment to official UN backing gives hope that international standards and “minimum guardrails” could eventually emerge to address AI risks, from military misuse to ethical safeguards.

What this means for the future of AI and global security

I found it interesting when several Nobel laureates and AI leaders signed an open call urging the UN to take charge of creating binding treaties on AI safety. They highlighted the urgent need to manage AI’s most “unacceptable risks” internationally, pointing to the risks of unchecked AI militarization and misinformation disasters.

The UN’s new forum and panel won’t eliminate AI’s challenges overnight, but they represent a critical turning point—moving from scattered national policies and summits toward coordinated, inclusive governance. For a technology as powerful and fast-moving as AI, global collaboration is the only way to ensure it benefits everyone rather than becoming a new source of conflict or injustice.

As a takeaway, it’s clear that AI governance is no longer a niche topic for tech insiders but a global concern demanding collective wisdom and action. Watching how the UN’s new structures develop will be fascinating—could this finally be the platform to prevent the worst of AI’s harms?

• AI governance needs global collaboration to address risks that no one country can manage alone.
• Human oversight in military AI applications is non-negotiable to prevent escalations or accidents.
• The UN’s new expert panel and forum may set minimum international standards that influence future AI safety regulations.

For those of us fascinated by AI’s impact on the world, the unfolding story of UN-led governance efforts is one to watch closely. It’s a reminder that technology alone won’t determine our future—our collective choices and policies will.

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AI and film have always had an evolving relationship, but lately, it feels like the pace of change is accelerating faster than ever. I recently discovered Runway‘s new AI tool called Aleph and it’s poised to rewrite the rules of visual effects (VFX) as we know them.

Imagine a tool where you upload your video footage, and through a simple conversation-like prompt, you can transform everything—add crowds, change lighting, swap objects, or even generate new camera angles and next shots. No painstaking frame-by-frame editing, no complex software juggling. Just natural language guiding your AI assistant to reshape your scenes. Sounds like sci-fi? Well, it’s here now, and it’s called Aleph.

What does this mean for filmmakers?

From a practical perspective, Aleph isn’t perfect yet. The AI-generated crowd might look a little eerie or “cursed” (think a Stranger Things character mashup), and subtle details like rain or lip-syncing sometimes miss the mark. However, big objects and broad scene changes perform surprisingly well. Backgrounds, lighting direction, and even complex effects like explosions can be prompted and adjusted easily.

More exciting is Aleph’s ability to generate new camera angles or shots based on existing footage. For instance, if you have one or two clips, you can ask Aleph to predict what a subsequent shot in that sequence might look like. Yes, there are continuity hiccups—lighting inconsistencies or framing slips—but the technology is close enough to act as a creative springboard, not just a tool for perfection. In fact, that imperfection might even spark more creative solutions and storytelling opportunities.

The rise of conversational video editing

What really caught my attention is the conversational experience—talking with your editing assistant like you might a fellow filmmaker. Want to add a sunset glow without drowning the natural look? Just ask. Need the explosion to start two seconds later? No problem. It’s a fresh way to engage with your edits and iterate rapidly without bouncing between different menus and toolsets.

And Runway isn’t alone. Another AI player, Luma, launched a similar feature called Modify Video, letting you prompt changes directly into your video footage. However, in tests, Luma’s outputs were less consistent—sometimes straying from the original footage, creating effects that felt disconnected or abstract. Meanwhile, Runway’s tool shines in rotoscoping and compositing—the kinds of detailed, pixel-level work that makes or breaks believable VFX.

Midjourney and AI video interpolation

Shifting gears, Midjourney rolled out a nifty feature called First Frame and Last Frame, which lets you set start and end images for a video, while the AI generates smooth motion interpolation between the two. It’s a cool way to craft cinematic transitions or experimental sequences, producing four versions at a time to choose from. For explorative creators, that’s a playground of possibilities—though fidelity still drops if you zoom in too much or push for longer sequences.

This interpolation pairs well with other tools for extending videos or incorporating motion effects, making Midjourney a strong candidate for early-stage storyboarding or mood-setting before moving into more detailed platforms like Runway or Luma for fine-tuning.

Open-source and other AI innovations in the filmmaking space

There’s also some exciting progress in open-source AI video generators. One 2.2 has gained traction for its temporal consistency and compatibility with existing training models. Although it requires a beefy GPU (12GB+), creators with the right hardware can produce stable videos without the high costs associated with commercial tools. It’s great to see democratization happening alongside the big tech players.

Meanwhile, experiments with JSON prompting—a way to send more structured commands to AI—hint at a future where AI can understand and execute complex video instructions with more precision. Early results suggest this could meaningfully improve animation smoothness and creative control, helping bridge the gap between human intent and machine execution.

What’s next? AI films hitting the big screen

If all this AI-driven creation sounds futuristic, it’s already stepping into theaters. Runway is partnering with IMAX to showcase AI film festival finalists in cities across the US this August. It’s a bold sign that AI-generated content is no longer just a novelty or niche curiosity—it’s becoming part of mainstream film culture.

And for those wondering about character consistency, Ideogram’s character model is a promising tool for generating consistent AI characters across scenes, which has traditionally been a thorny problem.

Key takeaways for creatives eager to explore AI in filmmaking

• Conversational AI editing tools like Runway’s Aleph are transforming VFX by allowing quick, natural language changes to video footage.
• The technology is not yet flawless but is powerful enough for social media and online content, and it’s improving fast.
• Combining multiple AI tools—for example, Midjourney for storyboarding and Runway for detailed compositing—creates a smooth creative workflow.
• Open-source AI video generators enable creators with good hardware to experiment at low cost, helping democratize filmmaking.
• AI films are entering mainstream venues like IMAX, signaling broader acceptance and opportunities for creators.

Reflecting on the AI film wave

Exploring these AI tools feels like standing on the edge of a creative revolution. While the output isn’t quite silver screen ready yet, the rapid advancements remind me of early digital photography or 3D animation—once clunky and limited, now indispensable. What excites me most is the collaborative potential—imagine a future where your AI creative partner truly understands your vision and helps shape projects in real time.

For anyone passionate about film and technology, this is a moment to dive in, experiment wildly, and start reshaping the stories we tell and how we tell them. Runway’s ALEPH is just the beginning, and with features on the horizon, the future is bright—if a bit wild.

And if you’re curious to learn more or connect with other AI filmmakers, there are inspiring communities and workshops popping up worldwide—from Curious Refuge meetups in cities like Miami, Toronto, and Paris to film festivals in Nigeria, the very first AI film festival on the continent.

So, whether you’re a dedicated filmmaker, an AI enthusiast, or simply someone curious about where tech and creativity converge, keep watching this space. The AI-powered film revolution is not just coming—it’s happening now.

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The 2024 Olympic Games in Paris are going to be a historic event for not only athletic achievements but also how people watch the games. Intel, a leading technology company is bringing its new way of airing the Olympics that will be of high resolution with 8K quality. It’s like having a very high-definition television but even better.

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OBS and other partners are working with INTEL to ensure this happens. They are using hyperfast computers and nifty software to send live 8K video over the internet resulting in enhanced viewership at home almost as good as being present physically.

Special cameras located in all Olympic venues initiate the process. These capture live happenings in 8K which presents four times more details compared to the current 4K TVs. The video is then processed by Intel’s latest powerful computers that use artificial intelligence to compress such enormous data into it (the video). Within seconds this compressed video crosses continents.

To view an 8K stream, one will need an up-to-date Intel PC and a brand-new television set for watching it on there. By decoding the signal these devices can enable ultra-clear pictures on your TV screen.

This broadcasting technology is a major step forward. There used to be no possibility of sending out such high-quality videos via the Internet fast enough for them to arrive while they were still newsworthy. However, within Intel’s new systems, as was demonstrated by their compression rate, which could make things about a thousand times smaller while maintaining excellent quality and ensuring little delay time.

Intel has been making efforts towards improving Olympic broadcasts since some years ago. For instance, they streamed more than 400 hours of content during Tokyo Olympics by partnering with various stakeholders. Similarly, Beijing Olympics hosted VR feeds using 8K that had never been seen before.

The aim is to make streaming services like what happened during Paris Olympics become common in future events so that many people can enjoy them. However not everyone can watch in 8k now but the technology displayed during the Paris Olympics suggests that future sports broadcasting and other live events could be different.

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France is gearing up to build Europe’s most powerful classified supercomputer for defense AI, as announced by Armed Forces Minister Sébastien Lecornu at the Eurosatory defense show in Paris. This ambitious project aims to position France at the forefront of artificial intelligence for military applications.

The new supercomputer will be available not only to the Armed Forces but also to the Higher Education Ministry and other government departments. Additionally, French defense firms will be able to run AI solutions in a secure environment. While Lecornu did not disclose specific details about the supercomputer’s capacity, the project is slated for completion in 2025.

In March, France announced the reallocation of €2 billion from the 2024-2030 defense budget to bolster AI development. Lecornu emphasized the importance of AI in distinguishing between leading nations and those falling behind. “The challenge for the French team is to stand out in this field,” he said. “When it comes to military AI, we’ll be the European power that’s best prepared, devoting the most resources to it.”

Lecornu highlighted existing AI applications within the French military, such as the Caesar howitzer, which uses AI for target acquisition via drones—a capability refined from Ukrainian experiences against Russia. The French Air Force also incorporates AI in pilot training programs.

Lecornu mentioned that the ministry will adopt a model of capacity sharing with civilian applications similar to that used by the French Atomic Energy Commission in the 1960s. In March, the Armed Forces Ministry announced the formation of a ministerial agency for artificial intelligence in defense, known by its French acronym Amiad.

“Artificial intelligence is a revolution, comparable in many respects to the atom’s impact in the aftermath of World War II,” Lecornu said. He underscored the necessity of running AI on secure, classified networks to maintain confidentiality and security.

France is not alone in prioritizing military AI. The U.S. Department of Defense’s AI spending nearly tripled to $557 million in the year ending August 2023, according to a Brookings Institution analysis published in March.

This initiative positions France as a leader in defense AI, aiming to significantly enhance its military capabilities and maintain a strategic edge in the rapidly evolving field of artificial intelligence.

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