Christopher Bender’s Post

From the X-verse: another assessment of the latest Stanford AI report Top 10 Takeaways {condensed}: 1. AI beats humans on some tasks, but not all. AI beats human performance on in image classification, visual reasoning, & English understanding. It trails behind on more complex tasks like advanced math, visual commonsense reasoning & planning. 2. Industry dominates AI research. In 2023, they made 51 notable AI models, while academia nade 15, with 21 notable models from industry-academia collaborations in 2023 3. Training costs of SOTA AI have skyrocketed. OpenAI’s GPT-4 used an estimated $78M compute, while Google’s Gemini Ultra $191M 4. USA leads China, the EU, and the U.K. in top AI models. In 2023, 61 notable AI models originated from the U.S, outpacing the EU's 21 and China’s 15. 5. Robust and standardized evaluations for LLM responsibility are seriously lacking. (plug: use weightwatcher.ai) 6. Generative AI investment skyrockets. Despite a decline in overall AI private investment last year, funding for generative AI surged to $25.2 billion. Major players include: OpenAI, Anthropic, Hugging Face, and Inflection 7. AI is not hype. AI makes workers more productive and leads to higher quality work. AI’s impact on labor suggest that AI enables workers to complete tasks more quickly & with higher quality. AI’s has the potential to bridge the skill gap between low- and high-skilled workers. But without proper oversight , AI can lower performance. 8. Scientific progress accelerates even further, thanks to AI. 2023, however, saw the launch of many science-related AI applications— from AlphaDev, which makes algorithmic sorting more efficient, to GNoME, which facilitates the process of materials discovery. 9. AI regulation is the US sharply increases. r In 2023, there were 25 AI-related regulations, up from just one in 2016. Last year alone, the total number of AI-related regulations grew by 56.3%. 10. People across the globe are more cognizant of AI’s potential impact—and more nervous. A survey from Ipsos shows that, over the last year, the proportion of those who think AI will dramatically affect their lives in the next 3-5 years increased from 60% to 66%. 52% express nervousness toward AI products and services, a 13% rise from 2022. In America, Pew data suggests that 52% of Americans report feeling more concerned than excited about AI, rising from 37% in 2022. source: https://lnkd.in/gQ3_aU5P

In case you missed it, The National CIO Review® published a thought-provoking piece from David Lefkovits last week on the major phases of AI development, leading to the most recent phases of Transformative AI and the Sudden Hype of explosive progress linked with the growth of Generative AI. For CIOs and other senior technology professionals at software and tech-enabled businesses, the challenges and opportunities from Gen AI are two-fold: (1) In general, how to capture the benefits of Generative AI to improve workflows across the business, and (2) In particular, with respect to the Software Development Lifecycle, how to increase productivity and “flow state” among developers, while managing the legal, security, and compliance risks associated with developers using GenAI tooling such as specific-to-engineering GitHub Co-Pilot and general tools like ChatGPT. Looking at that second topic in more detail, we see similar recent trends as with GenAI use overall. Adoption is widespread: Recent surveys indicate at least 63% of developers and 97% of Security and DevOps specialists are now using Gen AI tooling (Sources: HeavyBit, 2023; Sonatype, 2023). Benefits are significant: productivity improvements range from 10-55% (Thoughtworks, 2023; GitHub 2022). Our own research at Sema indicates that improvements of 25-40% are achievable in the near term. Risks are clear: to share two examples, developers believe that AI written code is more secure when in fact it is less so (Stanford, 2023); and in the US and Germany companies will not get copyright protection on their code if too much of it is written with GenAI code (German Copyright Act; US Copyright Office, 2023).   David also noted that “The challenge now isn't just technological; it's also educational.” Our team at Sema couldn’t agree more in the GenAI coding context. The biggest challenge that organizations face with GenAI in coding is teaching: . teaching Engineers how to make the most of Gen AI tools while minimizing the risks, · teaching Engineering Managers how to be supportive but firm about capturing the value from GenAI, and · teaching compliance teams on how to measure and manage the risks to accomodate regulators, customers, and other stakeholders like insurers.

"The AI Evolution: Navigating the Maze of Progress and Promise" In my latest piece for The National CIO Review®, I explore the thrilling journey of AI, from its theoretical inception in the 1950s to today's groundbreaking innovations. This article isn't just a historical overview; it's a window into the transformative power of AI across various sectors. 👇 Please share your thoughts and experiences in the comments. Let's demystify AI together! #EnterpriseAI #DigitalTransformation #DemistifyingAI #Innovation #HumanAugmentation

Completed the "Understanding Artificial Intelligence" course! From foundational concepts to real-world applications, this course has equipped me with a solid understanding of AI's potential and its implications across various industries. #AI #UnderstandingAI #ContinuousLearning

Understanding AI's transformation is crucial. I recently followed the training "Generative AI vs. Traditional AI" by Doug Rose, which offered enlightening insights: 📜 unpacking the history and basics of predictive AI: how can its evolution inform future tech advancements? 🧠 the emergence of self-supervised learning and the power of large language models: #ChatGPT exemplifies learning from vast text data; 🔍 selecting AI tools strategically, *beyond their popularity*, to solve unique industry challenges;  ⚖️ challenges in training models and the balance between simplicity and accuracy; 🎨 the fascinating shift to generative AI: think of how AI can transform simple sketches into detailed artwork, pushing creative boundaries; 🤖 ethical considerations in AI development, emphasizing the need for responsible use: the "stochastic parrot" analogy highlights the ethical need for AI to understand context, not just mimic language. With AI deeply embedded in our interactions, it's crucial to better understand the recipe of what we're consuming! #ArtificialIntelligence #MachineLearning #GenerativeAI #EthicalAI #TechTrends #Innovation #DataScience #AILearning #DigitalTransformation

NEW: Report on Generative AI 🤖 From economic shifts to potential job displacement, Oxford Martin researchers explore the transformative potential of Generative AI in insightful Citi report. Find out more: https://lnkd.in/eF_38_dE

Clearly this very brief article is just the start of the conversation, but it certainly encourages me to learn more about what Fei-Fei Li is doing to make sure we take a human-centered view of AI as she’s quoted saying, “It’s (AI) a very, very powerful technology, just like the inflection points that humanity has experienced in our civilization’s history, whether it’s fire or electricity or the PC—this is that scale and depth.” #ai #humancenteredartificialintelligence #stanfordresearch #lifelonglearning

🚀 Excited to share my latest blog post on the illuminating journey through artificial intelligence as presented in Melanie Mitchell's "Artificial Intelligence: A Guide for Thinking Humans." 📘💡 In this era where AI shapes much of our digital landscape, Mitchell's work stands out as a beacon, guiding us through the complexities and wonders of AI with clarity and insight. From the foundational mechanisms like neural networks and backpropagation to the ethical considerations at the heart of AI development, this book is a profound call to engage with AI beyond mere fascination. 🔍 I delve into how Mitchell makes AI accessible to all, bridging the gap between complex technical concepts and the everyday reader. The journey through AI's history, from Turing's pioneering thoughts to the deep learning renaissance, offers a rich tapestry of technological evolution and the relentless pursuit of mimicking human intelligence. But more than just an exploration of AI's capabilities, the post reflects on the critical ethical landscapes we navigate as AI becomes ever more integrated into our lives. It underscores the imperative of interdisciplinary collaboration and collective wisdom in steering AI towards a future that enhances human potential, upholds our shared values, and fosters equity and justice. Join me in contemplating our role in the narrative of AI, armed with informed curiosity and a commitment to ethical principles. Let's shape a future where technology advances humanity in all the right ways. 🌐✨ Read the full article here: https://lnkd.in/gSVxE2Md #ArtificialIntelligence #EthicalAI #MachineLearning #DeepLearning #Technology #Innovation

AI's rapid ascent continues! In an astounding revelation by 𝑺𝒕𝒂𝒏𝒇𝒐𝒓𝒅'𝒔 𝑯𝑨𝑰, 𝑨𝑰 has 𝒆𝒄𝒍𝒊𝒑𝒔𝒆𝒅 𝒉𝒖𝒎𝒂𝒏𝒔 in several performance benchmarks. From image recognition to reading comprehension, visual reasoning, and even complex problem-solving, AI is reshaping what we thought was possible. The latest AI Index report calls for a new generation of tests as current benchmarks no longer measure AI’s upper limits but our human advantages. It's a clarion call for innovators and policymakers to realign with this AI-driven epoch. Dive into the full report below. Stay tuned with us for the latest updates. #ai #innovation #artificialintelligence #technews #trendingupdates

As the field of AI evolves at a rapid pace, staying informed about the latest developments, trends, and ethical considerations is essential for professionals, researchers, and enthusiasts alike. In this article, we’ll explore 10 must-read Artificial Intelligence Books in 2024 that offer valuable insights, perspectives, and knowledge for navigating the complex and dynamic landscape of AI. #artificialintelligence #technology #aiinnovation #aibooks2024 #focusgts