Good morning, itās Friday. Microsoft is gearing up for GPT-4.5 and GPT-5, Figureās humanoid robot is learning to assist at home (finally, a roommate who might actually do the dishes), and Trump is planning more layoffs.
Plus, AI and robotics are filling labor gapsābut will they replace blue-collar jobs? In todayās Forward Future Original, we explore automationās growing role in manufacturing, elder care, and beyond.
š¤ FRIDAY FACTS
Can an AI system forget things? Unlike humans, AI doesnāt have memory in the traditional senseābut does that mean it never forgets? The answer might surprise you!
Stick around to find out more! š
šļø YOUR DAILY ROLLUP
Top Stories of the Day
š Microsoft Preps for GPT-4.5 & GPT-5
Microsoft is gearing up to host OpenAIās upcoming GPT-4.5, codenamed āOrion,ā which could launch next week, offering a major upgrade over GPT-4. Meanwhile, GPT-5 is expected by late May, integrating OpenAIās o3 reasoning model for even greater advancements. OpenAIās goal is to unify its AI models, reducing confusion and pushing closer to AGI, making its technology more seamless and powerful across applications.
š¤ Figureās Robot Learns to Assist at Home
Figure Robotics has unveiled Helix, a Vision-Language-Action (VLA) model that allows humanoid robots to understand voice commands and complete household tasks. Helix enables robots to visually assess their surroundings and respond, such as retrieving objects. Unlike traditional robots, it generalizes tasks for unseen items. Still in development, Figureās push into home robotics signals a long-term vision for AI-driven household automation.
š Trump Plans AI & Chip Agency Layoffs
The Trump administration is moving to cut up to 500 employees at NIST, the agency overseeing AI and semiconductor policy. Commerce Secretary Howard Lutnick is reviewing Biden-era tech programs, including $39 billion in semiconductor incentives and $11 billion in R&D. Part of Trumpās effort to shrink government, the layoffs spark concerns over research setbacks and brain drain. Lawsuits alleging executive overreach have already been filed, challenging the decision.
ā” Global Power Demand Soars Beyond AI
Electricity demand jumped 4.3% in 2024 and is projected to rise nearly 4% annually through 2027, driven mainly by China, India, and Southeast Asia. While AI data centers fuel demand spikes in the U.S. and Europe, the biggest contributors globally are air conditioning, EVs, and heavy industry. Solar and renewables are growing fast, but fossil fuel plants remain dominant. Cutting emissions will require replacingānot just supplementingāexisting power sources.
š° AI Hiring Startup Mercor Hits $2B
Mercor, an AI-driven hiring startup led by 21-year-old Thiel Fellow Brendan Foody, has skyrocketed to a $2 billion valuation after raising $100 million in a round led by Felicis. Founded in 2023, the company is already profitable, expecting $7 million in revenue and $1 million in profit this month. Investors, eager to secure a stake in AIās rapid expansion, finalized the deal in just two weeks, highlighting the intense demand for AI-driven businesses in todayās market.
āļø POWERED BY NVIDIA
New GeForce RTX 5090 GPUs Powering AI
NVIDIA GeForce RTX 50 Series GPUs unlock next level AI capabilities in digital humans, content creation, productivity, and development. From NIM microservices and AI Blueprints, to running local LLMs, image generation and more ā AI is optimized for use and accelerated on NVIDIA GPUs.
š ETHICS
Bridging Philosophy and AI: MITās New Ethics of Computing Course
The Recap: MITās new course, Ethics of Computing (6.C40/24.C40), blends philosophy and computer science to tackle the moral challenges of AI and technology. Co-taught by computing professor Armando Solar-Lezama and philosopher Brad Skow, the course challenges students to think critically about ethical dilemmas in AI, internet governance, and decision-making in the digital age.
Solar-Lezama invokes the myth of King Midas to highlight unintended consequences in programming, echoing concerns about AIās unpredictable impact
Students grapple with AI bias, free will, internet governance, and accountability in autonomous systems, like who is morally responsible when a self-driving car causes harm
Professors attend each otherās lectures, adjusting discussions in real-time to ensure interdisciplinary depth
A session on the controversial COMPAS algorithm sparks discussion on procedural versus substantive fairness, revealing the complexity of defining bias in AI systems
Students like Alek Westover and Caitlin Ogoe explore AI ethics beyond coding, asking deep questions like whether AI should be paid wages.
Forward Future Takeaways:
As AI continues to shape society, courses like Ethics of Computing are crucial in preparing the next generation of tech leaders to think beyond technical feasibility and consider ethical responsibility. By merging philosophical inquiry with engineering, MIT is fostering a new breed of thinkers who can navigate the moral complexities of AI, ensuring that technological advancements align with human values. ā Read the full article here.
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š¾ FORWARD FUTURE ORIGINAL
The Blue-Collar Worker and AI
āOne area humans are likely to maintain a relative (or even absolute) advantage for a significant time is the physical world. Thus, I think that the human economy may continue to make sense even a little past the point where we reach āa country of geniuses in a datacenterā. However, I do think in the long run AI will become so broadly effective and so cheap that this will no longer apply. At that point our current economic setup will no longer make sense, and there will be a need for a broader societal conversation about how the economy should be organized.ā
Dario Amodei, Machine Loving Grace
The ongoing integration of artificial intelligence and robotics into the labor market is increasingly affecting blue-collar occupations, i.e. jobs that traditionally involve manual labor. While some industries are already seeing significant progress, other areas are still facing challenges that make full automation difficult.
A key issue in this context is the shortage of skilled workers, which poses significant problems for many industries. Demographic change is leading to an aging society, with fewer and fewer young people entering the labor market. At the same time, quality and efficiency requirements are increasing, which in turn increases the demand for qualified workers. In this context, the use of AI and robotics offers a promising solution to close the gap between supply and demand. ā Continue reading here.
š§āš» CHIPS
AI-Designed Chips Defy Human Logic but Outperform Traditional Designs
The Recap: Researchers at Princeton Engineering and the Indian Institute of Technology used AI to design complex wireless chips in mere hoursāan achievement that would take human engineers weeks. The AI-created chips performed better than traditional designs but were structured in ways that human designers couldn't fully comprehend.
Instead of using human-engineered templates, the AI employed an inverse design method, working backward from desired performance metrics.
The resulting chip structures appeared random and incomprehensible to human engineers but proved more efficient than standard designs.
Manufacturing tests confirmed that AI-generated designs outperformed traditional ones in key performance areas.
Some AI-generated designs failed, drawing parallels to AI "hallucinations" seen in generative models.
The technology could revolutionize not just chip design but broader electronics engineering.
Forward Future Takeaways:
AI-driven chip design is still in its early stages, but its potential to accelerate innovation is undeniable. While human oversight remains necessary to correct errors, the ability to generate highly optimized, novel structures could lead to breakthroughs in computing, telecommunications, and energy efficiency. As AI continues to push past human intuition, the future of hardware design may become increasingly alienāyet astonishingly effective. ā Read the full article here.
š°ļø NEWS
Looking Forward: Stories Shaping the Future
šø Codeium Raising Funds at $2.85B: AI coding startup Codeium is securing new funding led by Kleiner Perkins, tripling its valuation in six months. With $40M ARR, it focuses on enterprise clients and agentic AI coding tools.
š§ Spotify Expands AI Audiobooks with ElevenLabs: Spotify now accepts AI-narrated audiobooks using ElevenLabs, boosting its audiobook library. Authors can generate recordings in 29 languages, though industry debates continue.
š OpenAI Hits 400M Weekly Users: OpenAI now serves 400M users weekly, up from 300M in December. Enterprise adoption is booming, with 2M paying business users and developer traffic doubling in six months.
š¤ NVIDIA Launches AI Tool for ASL: NVIDIA's free platform, Signs, uses AI and 3D avatars to teach American Sign Language with real-time feedback. Initially offering 100 signs, it aims to expand to 1,000.
š½ļø VIDEO
The Industry Reacts to Grok-3 - Speed Is All You Need
Grok 3 debuts as a top AI model, impressing experts with its rapid development and performance. Industry leaders highlight its strong benchmarks, supercomputer speed, and future potential, while early reviews praise its capabilities against top competitors. Get the full scoop in Mattās latest video! š
š¤ FRIDAY FACTS
AI Can āForgetā ā But Not Like You Think!
While AI doesnāt forget in the way humans do, it can lose information through a process called catastrophic forgetting. This happens when a machine learning model is trained on new data, overwriting old knowledge instead of integrating it. Think of it like studying for a new test and accidentally erasing everything you knew about last weekās exam!
To combat this, researchers use techniques like continual learning and memory replay, where old data is periodically revisited to prevent AI from completely wiping out past knowledge. So, while AI doesnāt forget because itās distracted or tired (lucky for it), keeping its knowledge intact is still a major challenge!
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The Forward Future Team
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