Topics covered in this episode include AI2's new OPEN large language models (OLMo), the alchemical model merging craze, model weight leaks from Mistral, challenges in moderating 'waifu' content, observations on the series True Detective, bias in models, and naming the listeners
Open language models (OLMs) like OMO promote inclusivity and collaboration in AI research.
Model merging in AI can enhance performance, but effective monitoring is crucial to balance experimentation and responsible use.
Deep dives
Open Language Models: The Power of Openness
Open language models (OLMs), such as LMAI's OMO, are gaining attention in the AI community. OMO stands for Open Model, Language Model, and it represents the release of pre-trained language models along with the necessary code and data. This level of openness allows for more experimentation and research in the field. While OMO's performance may not surpass models like Mistral, it opens up possibilities for analyzing the efficiency and scalability of models based on the amount of data they process. This move towards openness in language models is a significant step in promoting inclusivity and collaboration in AI research.
Model Merging and the Dark Side of AI
In the world of AI, model merging has become a popular and experimental practice. By combining two or more models through various techniques, researchers can improve the performance and capabilities of these models. However, there are potential risks associated with model merging, especially when it comes to generating questionable or inappropriate content. The waifu research department, a community known for merging different anime styles to create unique characters, is an example of the challenges and potential dangers this practice can bring. The need for effective monitoring and moderation systems becomes crucial to strike a balance between experimentation and responsible use of AI.
The Alchemical Journey of Founding and Building
The process of founding and building a company is often likened to an alchemical journey, involving transformation and personal growth. It requires deep self-reflection, attunement to one's own unconscious, and a commitment to the vision being pursued. Founders must navigate the delicate balance between manifesting their ideas in the world and sacrificing their own ego for the greater goal. This journey involves constant learning, vulnerability, and exposure, as well as alignment with a supportive organizational culture. While it can be challenging, the personal and spiritual transformation that comes with founding a company can be both scary and exciting.
The Intersection of Openness and Bias in AI
The concept of openness in AI goes beyond addressing model bias. It also involves creating an inclusive and equitable ecosystem for building and developing AI systems. The waifu phenomenon, which often highlights gender biases, serves as a reminder of the structural biases that exist in the AI community. Openness is a critical intervention in addressing these biases and fostering inclusion. While it poses challenges in terms of moderation, including systems for age verification and content monitoring, openness enables a wider range of voices and perspectives to be involved in shaping the narrative and impact of AI.
Wow, one of our favorites. This week Tom and Nate have a lot to cover. We cover AI2's new OPEN large language models (OLMo) and all that means, the alchemical model merging craze powering waifu factories, model weight leaks from Mistral, the calling card for our loyal fans, and more topics.
We have a lot of links you'll enjoy as you'll go through it: