OpenAI is funding research into ‘AI morality’

One of the leading AI companies is funding academic research into algorithms that can predict humans’ moral judgements.

Nov 24, 2024

In a filing with the IRS, OpenAI Inc., OpenAI’s nonprofit org, disclosed that it awarded a grant to Duke University researchers for a project titled “Research AI Morality.” Contacted for comment, an OpenAI spokesperson pointed to a press release indicating the award is part of a larger, three-year, $1 million grant to Duke professors studying “making moral AI.”

Little is public about this “morality” research OpenAI is funding, other than the fact that the grant ends in 2025. The study’s principal investigator, Walter Sinnott-Armstrong, a practical ethics professor at Duke, told TechCrunch via email that he “will not be able to talk” about the work.

Sinnott-Armstrong and the project’s co-investigator, Jana Borg, have produced several studies — and a book — about AI’s potential to serve as a “moral GPS” to help humans make better judgements. As part of larger teams, they’ve created a “morally-aligned” algorithm to help decide who receives kidney donations, and studied in which scenarios people would prefer that AI make moral decisions.

According to the press release, the goal of the OpenAI-funded work is to train algorithms to “predict human moral judgements” in scenarios involving conflicts “among morally relevant features in medicine, law, and business.”

NVIDIA CEO Jensen Huang, Unplugged

NVIDIA CEO Jensen Huang returned to his alma mater and interacted with the students of Hong Kong University Of Science & Technology. He opened up about everything, from the importance of AI, how AI evolved, NVIDIA's stock price and even how he wooed his wife by saying that he'll be CEO by the time he's 30! Watch Jensen Huang unplugged, like never before.

Veritone Introduces Data Refinery, Tackling AI’s Data Drought

In the fast-paced world of artificial intelligence, the data that fuels innovation is becoming increasingly scarce. But plenty of companies are sitting on mountains of unstructured data that could be used if processed appropriately.

Enter Veritone, Inc., intent on addressing this challenge with the introduction of Veritone Data Refinery. This new tool is designed to transform vast, unstructured datasets into polished, AI-ready assets—a critical step as industries push the boundaries of machine learning.

"So many organizations are trying to think about their 'GenAI strategy,' but a much more important and fundamental question is how to process the vast quantities of unstructured data and transforming it into something actionable and interpretable," said Dr. Christos Makridis, associate professor at Arizona State University and founder of Dainamic. “Platforms and services that empower organizations to make sense of their unstructured data — and most organizations have much more of it than they think — are going to be critical to reaping the benefits of the data revolution we're in.”

Confronting a Looming Data Shortage

The AI sector’s explosive growth has led to a voracious appetite for high-quality training data. But according to industry analyses, a significant shortage of accessible unstructured data looms on the horizon, with a crisis expected as early as 2026.

More about Veritone tackling AI’s data drought on Forbes

What is Artificial Superintelligence (ASI)?

Join Master Inventor Martin Keen as he explores the concept of Artificial Superintelligence (ASI), a hypothetical software-based AI system that is more advanced than any human. In this video Martin discusses the benefits of ASI, including decision making, problem solving, error reduction, and creativity, as well as the potential risks, including existential risk, automation, ethics, and goals.

We have partnered with Logictry AI to evangelize their products and services. Check out this case study with National Instruments, and learn how they utilized the platform to enable their internal sales team as well as their distributors and partners.

For more information about the Logictry platform, and use cases, please message me.

AI isn't hitting a wall, it's just getting too smart for benchmarks, says Anthropic

As their self-correction and self-reasoning improve, the latest LLMs find new capabilities at a rate that makes it harder to measure everything they can do.

Large language models and other forms of generative artificial intelligence are improving steadily at "self-correction," opening up the possibilities for new kinds of work they can do, including "agentic AI," according to the vice president of Anthropic, a leading vendor of AI models.

"It's getting very good at self-correction, self-reasoning," said Michael Gerstenhaber, head of API technologies at Anthropic, which makes the Claude family of LLMs that compete with OpenAI's GPT.

"Every couple of months we've come out with a new model that has extended what LLMs can do," said Gerstenhaber during an interview Wednesday in New York with Bloomberg Intelligence's Anurag Rana. "The most interesting thing about this industry is that new use cases are unlocked with every model revision."

The most recent models include task planning, such as how to carry out tasks on a computer as a person would; for example, ordering pizza online. "Planning interstitial steps is something that wasn't possible yesterday that is possible today," said Gerstenhaber of such step-by-step task completion.

Behind the Product: Replit | Amjad Masad

Amjad Masad is the co-founder and CEO of Replit, a browser-based coding environment that allows anyone to write and deploy code. Replit has 34 million users globally and is one of the fastest-growing developer communities in the world.

Prior to Replit, Amjad worked at Facebook, where he led the JavaScript infrastructure team and contributed to popular open-source developer tools. Additionally, he played a key role as a founding engineer at the online coding school Codecademy.

Small Bits, Big Ideas: The Amazing Rise Of 1-Bit LLMs For Building Faster And Slimmer Generative AI Apps

In today’s column, I explore the exciting and rapidly advancing realm of faster and slimmer generative AI that is being devised via the latest advances in so-called 1-bit large language models (LLMs). No worries if you don’t know what those are. I’ll be walking you step by step through what these emerging 1-bit LLMs are all about.

The topline aspect is that by devising generative AI based on this relatively new form of technological capabilities, you can astutely craft AI that works well under low-resource situations.

What is a low-resource situation? Imagine wanting to run a full-scale generative AI app entirely on your smartphone, doing so without having to engage any online or Internet connections. Envision a specialized edge device running standalone in a factory, fully loaded with a full-sized generative AI app tailored to doing factory work. And so on. Exhilarating times, for sure. Let’s talk about it.

More on 1-bit LLMs for faster and slimmer AI apps

How GenAI-Based Software Is Advancing Marketing and Sales

In this conversation, a16z Partner Seema Amble and a16z Podcast Host Steph Smith discuss the changing role of marketing in a $500 billion industry. In particular, they highlight how generative AI tools are reshaping everything from content creation to data-driven insights.

💡 Key Takeaways:

Shifting Roles: Marketers are moving from hands-on creators to strategic reviewers, empowered by AI-driven automation.
Game-Changing Tools: AI enables hyper-personalization, real-time research, and the seamless integration of sales and marketing.
Challenges Ahead: Trust, content quality, and brand consistency remain critical concerns for AI adoption.
Opportunities: AI can bridge gaps for SMBs, orchestrate marketing ecosystems, and unlock new efficiencies.

✅ Steps for Marketers: Experiment with AI-powered tools to streamline workflows. Focus on strategic decision-making by leveraging AI to automate routine tasks. Stay up to date on the latest developments in AI tech to maintain a competitive edge. 🔍

Discussion 📈With AI tools like Jasper and ChatGPT, marketing is no longer just about creation — it's about orchestration. Marketing teams can manage campaigns, drive customer engagement, or scale SMB solutions, and AI is rewriting the playbook.

Thats all for today, however new advancements, investments, and partnerships are happening as you read this. AI is moving fast, subscribe today to stay informed.