Author: hans
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Senior Managers and the AI Learning Curve
๐๐๐ง๐๐ซ๐๐ญ๐ข๐ฏ๐ ๐๐ ๐๐ง๐ ๐จ๐ญ๐ก๐๐ซ ๐๐ฆ๐๐ซ๐ ๐ข๐ง๐ ๐ญ๐๐๐ก๐ง๐จ๐ฅ๐จ๐ ๐ข๐๐ฌ (AI in general, digital platforms, blockchain, 3-D printing, etc.) pose a problem for ๐ฌ๐๐ง๐ข๐จ๐ซ ๐ฆ๐๐ง๐๐ ๐๐ซ๐ฌ. These technologies have far-reaching capabilities (partially surpassing those of humans) and are evolving rapidly, but they also come with significant risks. Senior managers, who have built their ๐๐ฑ๐ฉ๐๐ซ๐ญ๐ข๐ฌ๐ and associated ๐ฌ๐ญ๐๐ญ๐ฎ๐ฌ over the years,…
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Foundation Models for Numerical Tasks
1. Language models By now, we all know that large language models (LLMs) are very capable in qualitative and language-based tasks. The jury is still out, however, concerning their ๐ซ๐๐๐ฌ๐จ๐ง๐ข๐ง๐ ๐๐ง๐ ๐ง๐ฎ๐ฆ๐๐ซ๐ข๐๐๐ฅ skills. Researchers at the University of Chicago’s Booth School of Business (my alma mater) used ๐ ๐ข๐ง๐๐ง๐๐ข๐๐ฅ ๐๐ญ๐๐ญ๐๐ฆ๐๐ง๐ญ ๐๐ง๐๐ฅ๐ฒ๐ฌ๐ข๐ฌ (FSA) to test LLMsโ ability…
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Interpretable Features
A team at ๐๐ง๐ญ๐ก๐ซ๐จ๐ฉ๐ข๐, creator of the Claude models, published a paper about extracting ๐ข๐ง๐ญ๐๐ซ๐ฉ๐ซ๐๐ญ๐๐๐ฅ๐ ๐๐๐๐ญ๐ฎ๐ซ๐๐ฌ from Claude 3 Sonnet. This is achieved by placing a sparse autoencoder halfway through the model and then training it. An autoencoder is a neural network that learns to encode input data, here a middle layer of Claude, into…
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Chameleon, a mixed-modal early-fusion foundation model
In a new paper, Meta announces ๐๐ก๐๐ฆ๐๐ฅ๐๐จ๐ง, a ๐ฆ๐ข๐ฑ๐๐-๐ฆ๐จ๐๐๐ฅ ๐๐๐ซ๐ฅ๐ฒ-๐๐ฎ๐ฌ๐ข๐จ๐ง foundation model. Contrary to earlier multimodal models, which model the different modalities (text, image, audio, etc.) separately, mixed-modal early-fusion foundation models like Chameleon are end-to-end models. They ingest all modalities from the start and project them into one representational space. That permits integrating information across…
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A new report explores the economic impact of generative AI
I resisted the temptation to have a GenAI summarize theย ๐๐๐จ๐ง๐จ๐ฆ๐ข๐ ๐๐ฆ๐ฉ๐๐๐ญ ๐จ๐ ๐๐๐ง๐๐ซ๐๐ญ๐ข๐ฏ๐ ๐๐ย report by Andrew McAfee (MIT). At around 20 pages long (excluding references), the report delivers on the titleโs promise in less than one hour of reading. It explains how ๐๐๐ง๐๐ ๐ข๐ฌ ๐ ๐ ๐๐ง๐๐ซ๐๐ฅ-๐ฉ๐ฎ๐ซ๐ฉ๐จ๐ฌ๐ ๐ญ๐๐๐ก๐ง๐จ๐ฅ๐จ๐ ๐ฒ that is rapidly improving, becoming pervasive, and spurring…
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xLSTM: The inventors of LSTM are presenting a Transformer contender.
Has Sepp Hochreiter done it again? After months of announcements, a group around the inventor of the LSTM finally published a paper presenting ๐ฑ๐๐๐๐ to the world. Until the appearance of the Transformer in 2017, ๐๐๐๐ had been the go-to technology for a wide variety of sequence-related tasks, including text generation. Three limitations relegated LSTMs…
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GenAI’s copyright issues driving model diversity
This weekโs edition of the Economist (subscribers only) ran a feature on artificial intelligence and copyright. Generative AIs have been and continue to be trained on copyrighted material, including texts, images, music, videos, and more. Not all creators are amused. Some have chosen to sue the companies developing these Generative AI models. Others, including Associated…
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GenAI and the job market: a case for optimism
I resisted the temptation to have a GenAI summarize the ๐๐๐จ๐ง๐จ๐ฆ๐ข๐ ๐๐ฆ๐ฉ๐๐๐ญ ๐จ๐ ๐๐๐ง๐๐ซ๐๐ญ๐ข๐ฏ๐ ๐๐ report by Andrew McAfee (MIT). At around 20 pages long (excluding references), the report delivers on the titleโs promise in less than one hour of reading. It explains how ๐๐๐ง๐๐ ๐ข๐ฌ ๐ ๐ ๐๐ง๐๐ซ๐๐ฅ-๐ฉ๐ฎ๐ซ๐ฉ๐จ๐ฌ๐ ๐ญ๐๐๐ก๐ง๐จ๐ฅ๐จ๐ ๐ฒ that is rapidly improving, becoming pervasive, and…
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Fraunhofer launches FhGenie
The Fraunhofer Gesellschaft, one of Germany’s largest and most renowned research agencies, published a paper “FhGenie: A Custom, Confidentiality-preserving Chat AI for Corporate and Scientific Use“, in which the authors describe a customized chat AI, baptized FHGenie. The paper describes the motivation and requirements leading to the design, as well as the solution’s architecture. 1.…
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Techniques for using language models
One of the weaknesses of the models currently available on the market is that they have been trained on a publicly accessible data set, which may not necessarily be sufficient to meet certain specific needs. Take, for example, a company with a large volume of proprietary data, a highly specialized vocabulary or specific data formats.…