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Nov 28, 2024 | 
datafloq.com | Matthew McMullen
Large language models (LLMs) have advanced beyond simple autocompletion, predicting the next word or phrase. Recent developments allow LLMs to understand and follow human instructions, perform complex tasks, and even engage in conversations. These advancements are driven by fine-tuning LLMs with specialized datasets and reinforcement learning with human feedback (RLHF). RLHF is redefining how machines learn and interact with human inputs. What is RLHF?
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Jul 26, 2024 | 
datasciencecentral.com | Zachary Amos |Matthew McMullen |Dan Wilson
Predicting student performance is crucial for educational institutions aiming to enhance learning outcomes and provide timely support. Anticipating academic challenges and identifying at-risk pupils early allows schools to implement targeted interventions to improve success rates. Machine learning is crucial in this predictive process. It leverages vast amounts of educational data to uncover patterns and insights traditional analysis methods might miss.
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Jul 10, 2024 | 
dzone.com | Matthew McMullen
Large language models have played a catalytic role in how human language is comprehended and processed. NLP has bridged the communication gap between humans and machines, leading to seamless customer experiences. NLP is great for interpreting simple languages with straightforward intent. But it still has a long way to go when it comes to interpreting ambiguity in text arising from homonyms, synonyms, irony, sarcasm, and more.
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Jun 24, 2024 | 
datasciencecentral.com | David Stephen |Bill Schmarzo |Matthew McMullen
It is unlikely that AI safety for superintelligence and artificial general intelligence could be achieved directly without a track from current risks. Already, there are minute fractions of predicted existential threats of AGI that provide a map towards preparing for the unknowns, ahead. AI is a dynamic non-living thing.
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Jun 21, 2024 | 
datafloq.com | Matthew McMullen
Generative AI, even in its early stage of development, is disrupting the product design life cycle, influencing everything from the initial idea to the final design. While artificial intelligence has been used in design and manufacturing for over a decade, generative AI tools are more transformative and can significantly spark innovation. Generative AI has a wide range of applications in product design, from product packaging and automotive components to retail displays.
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Jun 16, 2024 | 
datasciencecentral.com | Bill Schmarzo |Kevin Vu |Matthew McMullen |David Stephen
“It’s not the AI technologies that fail; it’s the organization.”That might be a somewhat controversial viewpoint, but it emphasizes an important truth: Artificial Intelligence (AI) is a tool, not a living entity (apologies to movie enthusiasts) that will do what it is instructed and trained to do, thanks to the AI Utility Function.
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Jun 13, 2024 | 
datasciencecentral.com | Kevin Vu |Matthew McMullen |Dan Wilson |Bill Schmarzo
Foundational LLMs have read every byte of text they could find and their chatbot counterparts can be prompted to have intelligent conversations and be asked to perform specific tasks. Access to comprehensive information is democratized; No more figuring out the right keywords to search or picking sites to read from. However, LLMs are prone to rambling and generally respond with the statistically most probable response you’d want to hear (sycophancy) an inherent result of the transformer model.
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Jun 13, 2024 | 
datasciencecentral.com | Aileen Scott |Matthew McMullen |Ovais Naseem |Alan Morrison
Data science in today’s business world is serving as the lifeblood of decision-making. Be it optimizing marketing campaigns or predicting financial trends, data science comes in handy across all industries to make data-driven decisions. It empowers businesses and organizations to analyze huge amounts of raw data and get meaningful insights that can help them propel their businesses forward.
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Mar 18, 2024 | 
datasciencecentral.com | Ovais Naseem |Vincent Granville |Matthew McMullen
In the digital age, businesses are inundated with data. This bounty, however, isn’t confined to tidy rows and columns; it spills over as emails, social media interactions, video content, and more—forming a vast ocean of unstructured data. While this data can potentially harbor critical business insights, its nature makes it resistant to traditional analysis.
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Feb 29, 2024 | 
datafloq.com | Matthew McMullen
Machine learning models have been operating for a long time on a single data mode or unimodal mode. This involved text for translation and language modeling, images for object detection and image classification, and audio for speech recognition. However, it’s a well-known fact that human intelligence is not restricted to a single data modality as human beings are capable of reading as well as writing text. Humans are capable of seeing images and watching videos.
