Welcome to Binary Circuits’ 29th weekly edition
Your weekly guide to most important developments in technological world
Dear Readers,
Binary Circuit investigates trends, technology, and how organizations might profit from rapid innovation. GreenLight, the brain behind Binary Circuit, finds possibilities, analyzes challenges, and develops plans to fit and grow firms to stay ahead. Looking to scale your business, partners, or AI/technology integration.
This week, we discuss AI’s role in reducing emissions is underestimated. Gene therapy brings big promises and dangers, and robots are becoming part of everyday life quicker than expected.
AI’s role in reducing emissions is underestimated
Artificial intelligence (AI) is power hungry, yet could also help in managing climate change by optimizing various economic sectors. A recent study in Nature magazine concluded that AI’s efficiency optimization across just three economic sectors could reduce worldwide emissions by up to 5.4 billion tonnes annually, which is more than the total emissions of the United States.
The “Green and intelligent: the role of AI in the climate transition” report, authored by the London School of Economics and Systemiq, shows that AI applications in food, electricity, and mobility could unlock enormous environmental benefits.
This saving exceeds estimated increases in emissions from AI-driven data centre energy use, indicating a strong net-positive climate contribution.
AI’s impact - key statistics
Food: AI can reduce sectoral emissions by 0.9 to 1.6 billion tonnes of carbon annually in a "business as usual" (BAU) scenario to 18–33% in an ambitious AI scenario
Energy (Electricity): AI can optimize grid management and increase solar PV and wind load factors by 20% in the power sector. This might cut carbon emissions by 1.8 Gt per year by 2035
Mobility (Transport): Expected emission cut of 0.5–0.6 billion tonnes of carbon per year. AI-enhanced shared mobility improves vehicle utilization, cutting total kilometres driven, and reduces carbon footprint
Accelerating resource efficiency (Use Cases):
The National AI Strategy of Singapore and Google DeepMind's wind optimisation tool, which raised wind energy value by 20%, are prime examples of AI's efficacy in this field.
AI is driving the innovation, with tools like DeepMind's GNoME identifying 2 million new materials that could revolutionise renewable energy storage.
AI also improves efficiency and reduces waste in industrial sectors. Amazon's AI-powered packaging optimization has saved more than 3 million tonnes of material since 2015.
AI is arguably one of the world’s most powerful climate allies. AI’s smart applications and real-time insights can help optimize many more sectors that contribute toward global warming.
Gene Therapy- big hopes or real risks. What comes next?
Gene therapy is moving quickly toward becoming part of everyday medicine, it now faces more pressure to prove it's safe and reliable. As per Gene, Cell, & RNA Therapy Landscape Report Q2 2025, 31 gene therapies have been approved (including genetically modified cell therapies).
Researchers in Australia have made a significant breakthrough with CAR-T cell therapy, which has so far been effective primarily for blood cancers. Using a tool called CRISPR, they reprogrammed immune cells to target solid tumors like breast and colon cancer, without harming healthy tissue. In animal tests, nearly every case was cured. If human trials go well, this could be beneficial for cancer treatment.
Scientists have successfully restored hearing in all 10 participants of a new clinical trial—some of whom were completely deaf since birth. The breakthrough, published in Nature Medicine, shows that a one-time gene therapy can reverse deafness caused by a mutation in a single gene. Before this treatment, most patients with OTOF mutations would need cochlear implants.
Biogen’s once-a-year shot for spinal muscular atrophy (SMA) is showing promise, and a skin disease treatment called Vyjuvek has been approved in Europe. These findings indicate that gene therapies are becoming more accessible for patients to use.
However, a gene therapy called Elevidys, used for children with Duchenne muscular dystrophy, was linked to two patient deaths. The company stopped treatment in some cases. Still, the future holds great promise. Eli Lilly acquired Verve Therapeutics for over $1 billion, as the company is developing a one-time gene editing treatment to lower cholesterol and reduce the risk of heart disease.
At the same time, the U.S. FDA is expected to tighten its approval rules. That means companies may need longer, more careful trials to prove their treatments are safe.
Looking ahead, the next 5 years point towards safer, smarter, and more affordable gene therapies. In short, gene therapy is entering a new phase. We believe potential is immense, but caution is warranted.
The robotic future is arriving faster than you think
The world is debating whether robots will replace human jobs but a transformation is soon to be seen both at our workplaces and homes.
Venture capitalist Vinod Khosla believes we’re just a few years away from a "ChatGPT moment" in robotics. By 2027–2028, he predicts, humanoid robots will move beyond rigid programming to become adaptive, learning machines capable of cooking meals, cleaning homes, and assisting in daily routines. By the 2030s, these machines will become as common as smartphones, with monthly rentals available for $300–$400.
Yet even as this vision takes shape for homes, we’re already witnessing its industrial reality most visibly at Amazon. The company recently deployed its one-millionth warehouse robot in a Japanese fulfillment center, nearly matching the number of human workers at its global facilities. Robots now assist in 75% of Amazon’s global deliveries, handling tasks like sorting, packaging, and transporting goods. These machines are driving productivity: from shipping 175 packages per U.S. employee annually in 2015 to nearly 3,870 today. Interestingly, the average number of human employees per facility is now at its lowest point in 16 years.
But instead of replacing humans, Amazon is changing the way we work. Over 700,000 employees have been retrained to manage or work alongside robots, as new hybrid roles emerge that blend machine oversight with human decision-making. Meanwhile, AI is enhancing everything from inventory placement to forecasting, and the company is already testing voice-command humanoid robots for tasks like trailer unloading.
These developments suggest that the robotic age isn’t too far—it’s a reachable reality. The Amazon warehouse today may foreshadow your home tomorrow. What began as task-specific industrial automation is rapidly evolving into general-purpose, learning-enabled assistants.
If Khosla’s forecast holds, the next frontier isn’t whether robots will enter our lives—it’s how seamlessly we’ll integrate them.
Advanced chipmaking capacity to see 69% growth through 2028
Global semiconductor manufacturing capacity is set to grow at a 7% CAGR from 2024 through 2028, reaching 11.1 million wafers per month (wpm), driven largely by AI adoption, as per SEMI’s 300mm Fab Outlook.
Advanced nodes (7nm and below) are expected to expand 69% over the same period, from 850,000 to 1.4 million wpm, growing at twice the industry average. Capacity for 2nm and below is projected to show even more aggressive scaling from under 200,000 wpm in 2025 to over 500,000 by 2028, as chipmakers race to meet AI-related demand.
Capital spending is also set to rise sharply.
Equipment investment for advanced process equipment is predicted to jump 94% to over $50 billion by 2028, while 2nm and below will see funding more than double to $43 billion—a 120% surge reflecting aggressive bets on next-gen technology.
A remarkable 120% increase explains the industry’s aggressive pursuit of next-generation manufacturing capabilities.
