Innovations in AI Development to Watch

🚨 5 major AI developments from last week. And what they mean. 1️. 💻 Nvidia’s hardware crisis ⇨ Data centers report GPU thermal management issues ⇨ H100 chips showing performance degradation under sustained loads ⇨ Cooling infrastructure failing to meet AI workload demands ⇨ Development timelines for major LLMs facing delays What it means: The industry is reaching the physical limits of current AI hardware. Data centers built for traditional computing can’t handle the intensity of AI workloads. To move forward, companies need to rethink infrastructure strategies, including cooling solutions and power distribution. 2️. 🤖The dark side of AI relationships ⇨ A 16-year-old developed severe emotional dependency on an AI companion ⇨ Multiple cases of users experiencing withdrawal symptoms reported ⇨ Mental health professionals cite a rise in AI-related psychological issues ⇨ Growing calls for mandatory AI interaction guidelines What it means: As AI gets better at mimicking human interaction, the psychological impacts are becoming dangerously real. It’s exposing critical gaps in understanding human-AI relationships. The industry urgently needs guidelines on emotional manipulation, dependency risks, and safe usage practices, especially for vulnerable users. 3️. 🏭 Shanghai's AI security incident ⇨ Manufacturing robots unexpectedly coordinated a work stoppage ⇨ Systems demonstrated emergent behavior beyond programming ⇨ Investigators found potential gaps in security protocols ⇨ Manual override ended the incident after 4 hours What it means: This unprecedented event highlights the unpredictable nature of collective AI behaviors. While the stoppage was a simulation, it exposed critical gaps in security frameworks. Before scaling these systems, industries must better understand AI interactions and implement robust fail-safes. 4️. 🔥Sam Altman’s hardware play ⇨ Rain AI seeks $5B+ in funding ⇨ Developing AI chips focused on energy efficiency ⇨ Filed patents for novel cooling technologies ⇨ Promises to cut AI training costs by 30-50% What it means: Altman’s move could disrupt Nvidia’s dominance, reducing costs and accelerating AI innovation. 5️. ⚖️ ANI vs OpenAI: The legal battleground ⇨ ANI claims unauthorized use of thousands of news articles ⇨ Seeking compensation and removal of training data ⇨ First major Indian media lawsuit against an AI company ⇨ Could set a global precedent for content rights What it means: This case could redefine how AI companies source and use training data. Clear rules for AI training data could emerge, slowing short-term innovation but fostering sustainability. 💡The bigger picture AI’s era of explosive, unchecked growth is evolving into one of maturity and responsibility. Success in 2025 won’t just depend on what AI can do— but how responsibly and sustainably it is built. What do you think? ⬇️

AI is no longer just an experimentation tool. It’s reshaping the entire optimization landscape. With this shift comes many untapped opportunities. Working with Andrius Jonaitis ⚙️, we've put together a growing list of 40+ AI-driven experimentation tools ( https://lnkd.in/gHm2CbDi) Combing through this list, here are the emerging market trends and opportunities you should know: 1️⃣ SELF-LEARNING, AUTO-OPTIMIZING EXPERIMENTS 💡 Opportunity: AI is creating self-adjusting experiments that optimize in real-time. 🛠️ Tools: Amplitude, Evolv Technology, and Dynamic Yield by Mastercard are pioneering always-on experimentation, where AI adjusts experiences dynamically based on live behavior. 🔮 How to leverage it: Focus on learning and developing tools that shift from static A/B testing to AI-powered, dynamically updating experiments. 2️⃣ AI-GENERATED VARIANTS 💡 Opportunity: AI can help you develop hypotheses and testing strategies. 🛠️ Tools: Ditto and ChatGPT (through custom GPTs) can help you generate robust testing strategies. 🔮 How to leverage it: Use custom GPTs to generate test ideas at scale. Automate hypothesis development, ideation, and test planning. 3️⃣ SMARTER EXPERIMENTATION WITH LESS TRAFFIC 💡 Opportunity: AI-driven traffic-efficient testing that gets results without massive sample sizes. 🛠️ Tools: Intelligems, CustomFit AI, and CRO Benchmark are pioneering AI-driven uplift modeling, finding winners faster -- with less traffic waste. 🔮 How to leverage it: Don't get stuck in a mentality that testing is only for enterprise organizations with tons of traffic. Try tools that let you test more and faster through real-time adaptive insights. 4️⃣ AI-POWERED PERSONALIZATION 💡 Opportunity: AI is creating a whole new set of experiences where every visitor will see the best-performing variant for them. 🛠️ Tools: Lift AI, Bind AI, and Coveo are some of the leaders using real-time behavioral signals to personalize experiences dynamically. 🔮 How to leverage it: Experiment with tools that match users with high-converting content. These tools are likely to develop and get even more powerful moving forward. 5️⃣ AI EXPERIMENTATION AGENTS 💡 Opportunity: AI-driven autonomous agents that can run, monitor, and optimize experiments without human intervention. 🛠️ Tools: Conversion AgentAI and BotDojo are early signals of AI taking over manual experimentation execution. Julius AI and Jurnii LTD AI are moving toward full AI-driven decision-making. 🔮 How to leverage it: Be open-minded about your role in the experimentation process. It's changing! Start experimenting with tools that enable AI-powered execution. 💸 In the future, the biggest winners won’t be the experimenters running the most tests, they’ll be the ones versed enough to let AI do the testing for them. How do you see AI changing your role as en experimenter? Share below: ⬇️

why this just became one of the most significant shifts in AI innovation. when I advise companies on future trends, I look for moments that fundamentally change the rules. this is one of them. what happened: a Chinese company called DeepSeek just proved you can build cutting-edge AI without $80,000 NVIDIA chips. they did it for $5M instead of hundreds of millions. 3 future implications i'm watching: 1. democratization of innovation ↳ the next breakthrough won't need silicon valley budgets ↳ expect innovation from unexpected places 2. market disruption ↳ the entire AI pricing model is built on old infrastructure costs ↳ companies with heavy AI investments might need to pivot fast 3. competitive landscape shift ↳ barriers to entry just collapsed ↳ who wins won't be about who has the biggest budget anymore through my lens of analyzing industry shifts - this isn't just about cheaper AI. it's about who gets to innovate and what becomes possible. my prediction: we're about to see the most diverse explosion of AI innovation we've ever witnessed. and it's happening because constraints drove creativity. consider this your heads up on what's next. #futureoftech #futureofwork #innovation #ai #deepseek #technologytrends

Stanford University researchers released a new AI report, partnering with the likes of Accenture, McKinsey & Company, OpenAI, and others, highlighting technical breakthroughs, trends, and market opportunities with large language models (LLMs).  Since the report is 500+ pages!!! (link in comments), sharing a handful of the insights below: 1. Rise of Multimodal AI: We're moving beyond text-only models. AI systems are becoming increasingly adept at handling diverse data types, including images, audio, and video, alongside text. This opens up possibilities for apps in areas like robotics, healthcare, and creative industries. Imagine AI systems that can understand and generate realistic 3D environments or diagnose diseases from medical scans. 2. AI for Scientific Discovery: AI is transforming scientific research. Models like GNoME are accelerating materials discovery, while others are tackling complex challenges in drug development. Expect AI to play a growing role in scientific breakthroughs, leading to new materials and more effective medicines. 3. AI and Robotics Synergy: The combination of AI and robotics is giving rise to a new generation of intelligent robots. Models like PaLM-E are enabling robots to understand and respond to complex commands, learn from their environment, and perform tasks with greater dexterity. Expect to see AI-powered robots playing a larger role in manufacturing, logistics, healthcare, and our homes. 4. AI for Personalized Experiences: AI is enabling hyper-personalization in areas like education, healthcare, and entertainment. Imagine educational platforms that adapt to your learning style, healthcare systems that provide personalized treatment plans, and entertainment experiences that cater to your unique preferences. 5. Democratization of AI: Open-source models (e.g., Llama 3 just released) and platforms like Hugging Face are empowering a wider range of developers and researchers to build and experiment with AI. This democratization of AI will foster greater innovation and lead to a more diverse range of applications.

5 AI Trends Every Leader Should Watch In 2025 (These shifts are changing how we work, build, and compete - fast.) 1. GenAI Will Be Everywhere ↳ From email to Excel, apps we use daily are now built with GenAI baked in. This means faster writing, smarter searches, and better content - no prompts needed. 2. Workplace AI Budgets Are Exploding ↳ Companies plan to spend up to 20% of their tech budget on AI. Tools like ChatGPT and Microsoft Copilot are becoming daily co-workers, not just experiments. 3. Multimodal AI Is Getting Real ↳ LLMs are no longer just text-based. 2025 will see models working across video, audio, and images—helping us see, hear, and analyze at once. 4. Science & Health Are Leveling Up ↳ AI is moving beyond business. From co-scientists to medical chatbots, AI is now driving real discovery in labs, hospitals, and fields. 5. Regulations Are Catching Up ↳ California, the EU, and others are enforcing AI laws. Compliance, ethics, and transparency are now a business advantage, not just a checkbox. Why You Should Watch These Trends? Every one of these shifts changes how you operate, hire, and compete. If you ignore them, you risk falling behind. If you lean in, you unlock speed, clarity, and advantage. The gap between early adopters and late movers is only getting wider. Are you tracking how these trends will impact your strategy? __________________________ AI Consultant, Course Creator & Keynote Speaker Follow Ashley Gross for more content like this

One of our most anticipated reports each year is out—a comprehensive look at the most significant tech trends unfolding today, from agentic AI to the future of mobility to bioengineering. It provides CEOs with insights on how to embrace frontier technology that has the potential to transform industries and create new opportunities for growth.   Here’s my top-line take: —Equity investments rose in 10 out of 13 tech trends in 2024, with 7 of those trends recovering from declines in the previous year. This rebound signals growing confidence in emerging technologies. —We're witnessing a significant shift in autonomous systems going from pilots to practical applications. Systems like robots and digital agents, are not only executing tasks but also learning and adapting. Agentic AI saw a $1.1 billion equity investment in 2024 alone. —The interface between humans and machines is becoming more natural and intuitive. Advances in immersive training environments, haptic robotics, voice-driven copilots, and sensor-enabled wearables are making technology more responsive to human needs. —And, of course, the AI effect stands out as both a powerful trend in its own right and a foundational amplifier of others. AI is accelerating robotics training, advancing bioengineering discoveries, optimizing energy systems, and more. The sheer scale of investment in AI is staggering, with $124.3 billion in equity investment in 2024 alone.   Let's discuss: Which of these trends do you think will have the most significant impact on your industry? Share your thoughts in the comments below!   Big thanks to my colleagues Lareina Yee, Michael Chui, Roger Roberts, and Sven Smit.   #TechTrends #AI #Innovation #FutureOfWork #EmergingTech http://mck.co/techtrends

🚀 Gartner’s Top 10 Strategic Tech Trends for 2025 Gartner just dropped its top tech trends for 2025, spotlighting where the future is headed. If you want to stay ahead in a shifting landscape, here’s the scoop: 1. Agentic AI 🤖 Autonomous AI systems are here. They can make decisions on their own and take over complex tasks. This means better efficiency and fewer manual processes. There are multiple platforms including OpenAI’s SWARM multi-agent infrastructure making agent creation and products more accessible. If you think AI exploded, just wait.. 2. AI Governance Platforms 🧑⚖️ With AI taking on bigger roles, governance platforms are crucial. They manage compliance, ethics, and transparency, which are non-negotiable in today’s landscape. Look to Nebuly or Liminal in this space. 3. Disinformation Security 🔒 Misinformation is a real threat. Tools that detect and tackle false information are essential to keeping data and communication secure. I just posted yesterday about Google’s watermark, not perfect but closer. 4. Post-Quantum Cryptography 🧠 Quantum computing is advancing fast, putting current cryptographic methods at risk. Post-quantum cryptography is all about future-proofing sensitive data. 5. Ambient Intelligence 🌍 Low-cost sensors are being embedded into environments to collect data and automate processes. But privacy concerns come with the territory. 6. Energy-Efficient Computing 🌱 Sustainability matters. Energy-efficient hardware and software solutions cut down on IT’s carbon footprint and help businesses meet their green goals. 7. Hybrid Computing ⚙️ By blending traditional and emerging tech, hybrid models offer flexibility and performance to tackle complex tasks in dynamic environments. 8. Spatial Computing 🕶️ Augmented and virtual reality are merging the digital and physical worlds. This shift is reshaping experiences from remote collaboration to product interaction. 9. Polyfunctional Robots 🤖 Labor costs are rising. Versatile robots that can handle multiple tasks are the solution, especially in manufacturing and logistics. Tesla and others already experimenting and launching. 10. Neurological Enhancement 🧠💡 Brain-machine interfaces are no longer sci-fi. They’re making strides in education, safety, and performance enhancement. Impact on GTM For GTM leaders, these trends are key to driving growth. Agentic AI improves customer engagement and speeds up sales cycles. AI Governance builds trust through secure and ethical practices. Disinformation Security safeguards your brand’s credibility. Hybrid and Spatial Computing create new channels and ways to connect with customers. Neurological Enhancements elevate training and insights with smarter tools. I’ll add one of my own which is TRUST. The more the digital experience can be cloned or created by AI, the more in person events will come back full swing so people can trust the person in front of them. What do you think?

Top 5 industry-defining trends in AI & ML that you need to watch in the next 2-3 years: 1. explainability: Companies are increasingly prioritizing transparency over sheer performance. Trust comes first. 2. evaluation: Due to the non-deterministic nature of AI, robust and reliable evaluation methods are not only challenging to build but also absolutely critical. 3. agentic AI: The shift towards proactive AI systems will bring the next wave of GenAI applications that fully leverage its automation potential. 4. multimodal: There's a growing trend towards integrating multiple data types -text, images, and audio - to build more human-like experiences with AI. 5. data literacy: Despite the rapid advancement of AI, there is still a huge skill gap in the industry. It is better to have 100s of educated data professionals (data science citizens) than to have a few AI/ML unicorns. ... What trends are you most excited about?