Targeting AI

著者: TechTarget Editorial
  • サマリー

  • Hosts Shaun Sutner, TechTarget News senior news director, and AI news writer Esther Ajao interview AI experts from the tech vendor, analyst and consultant community, academia and the arts as well as AI technology users from enterprises and advocates for data privacy and responsible use of AI. Topics are related to news events in the AI world but the episodes are intended to have a longer, more ”evergreen” run and they are in-depth and somewhat long form, aiming for 45 minutes to an hour in duration. The podcast will occasionally host guests from inside TechTarget and its Enterprise Strategy Group and Xtelligent divisions as well and also include some news-oriented episodes featuring Sutner and Ajao reviewing the news.
    Copyright 2023 All rights reserved.
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あらすじ・解説

Hosts Shaun Sutner, TechTarget News senior news director, and AI news writer Esther Ajao interview AI experts from the tech vendor, analyst and consultant community, academia and the arts as well as AI technology users from enterprises and advocates for data privacy and responsible use of AI. Topics are related to news events in the AI world but the episodes are intended to have a longer, more ”evergreen” run and they are in-depth and somewhat long form, aiming for 45 minutes to an hour in duration. The podcast will occasionally host guests from inside TechTarget and its Enterprise Strategy Group and Xtelligent divisions as well and also include some news-oriented episodes featuring Sutner and Ajao reviewing the news.
Copyright 2023 All rights reserved.
エピソード
  • AI industry could see regulation rollback under Trump
    2024/11/07
    President-elect Donald Trump during his election campaign offered clues about how his administration would handle the fast-growing AI sector. One thing is clear: AI, to the extent that it is regulated, is headed for deregulation. "It's likely going to mean less regulation for the AI industry," said Makenzie Holland, senior news writer at TechTarget Editorial covering tech regulation and compliance, on the Targeting AI podcast. "Being against regulation and [for] deregulation is a huge theme across his platform." Trump views rules and regulations on business as costly and burdensome, Holland noted. The former president and longtime businessman's outlook presumably includes independent AI vendors and the tech giants that also develop and sell the powerful generative AI models that have swept the tech world. President Joe Biden's wide-ranging executive order on AI has been the strongest articulation of how the federal government views AI policy. However, it's unclear which elements of the Democratic president's plan Trump will scrap and which he'll keep. Trump established the National Artificial Intelligence Initiative Office at the end of his first term as president in 2021. David Nicholson, chief technology advisor at Futurum Group, said on the podcast that Trump will likely retain some aspects of the executive order with bipartisan support. Among these is the federal government's recognition that it should guide and promote AI technology. "[Trump will] definitely not scrap it wholesale," Nicholson said. "There's something behind a lot of those concerns ... and pretty bipartisan concern that AI is a genie that we only want to let out of the bottle, if possible, very carefully." Holland, however, doesn't expect many regulatory proposals in Biden's executive order to survive the next Trump presidency. Trump is also likely to dramatically de-emphasize the AI safety concerns and regulatory proposals that feature prominently in Biden's executive order, she said. Meanwhile, concerning Elon Musk -- a major Trump backer and owner of the social media platform X, formerly Twitter, and generative AI vendor xAI -- the issue is complicated, Nicholson said. Musk has been a trenchant critic of xAI competitor OpenAI, alleging in a lawsuit that the rival vendor abandoned its commitment to openness in AI technology. However, Nicholson noted that Musk's definition of transparency in training large language models is unorthodox, insisting that models be "honest" and not contain political bias. "Having the ear of the president and the administration, I think he could be meaningful in that regard," Nicholson said. "[Musk] is going to be the loudest voice in the room when it comes to a lot of this stuff." While Trump is expected to try to reverse or ignore much of Biden's agenda, one major piece of bipartisan legislation passed during Biden's tenure, the CHIPS and Science Act of 2022, is likely to survive because it emphasizes reviving manufacturing and technology development in the U.S., Nicholson said. But the Federal Trade Commission's and Department of Justice's active stances on AI rulemaking and big tech regulation -- the DOJ successfully sued Google for monopolizing the search engine business -- are ripe for a Trump rollback. "The FTC is likely to face a shake-up, as far as Lina Khan's job probably is on the line," Holland said, referring to the activist FTC chair, who has vigorously pursued a number of big tech vendors. "Trump's entire platform is about deregulation and being against regulation. That's automatically going to impact these enforcement agencies, which, in some capacity, can make their own rules," Holland said. In the absence of meaningful federal regulation of AI, the U.S. is moving toward a state-by-state regulatory patchwork. Shaun Sutner is senior news director for TechTarget Editorial's information management team, driving coverage of artificial intelligence, unified communications, analytics and data management technologies. Esther Ajao is a TechTarget Editorial news writer and podcast host covering artificial intelligence software and systems. Together, they host the Targeting AI podcast series.
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    40 分
  • Exploring the role of AI in beauty and haircare
    2024/10/29

    When Candace Mitchell was young, she discovered a love for computers and haircare. Her interest in technology led her to study coding in high school, leading her to build websites.

    Meanwhile, she also considered going to cosmetology school.

    She found a middle ground in beauty technology, later becoming co-founder and CEO of Myavana, a Black-owned beauty technology vendor. Myavana uses AI technology to analyze hair strands and make haircare recommendations.

    Myavana started with a hair analysis kit; the startup's technology uses machine learning to identify and analyze the different unique combinations in people's hair.

    "Our research shows us that there are actually 972 unique combinations of hair profiles," Mitchell said on the latest episode of the Targeting AI podcast. "Using machine learning is how we can automate the process of the analysis and generate those product recommendations."

    While Myavana works with consumers, it found that its data on hair is also valuable to enterprises interested in the haircare business.

    "When you come to Myavana, you can target consumers based on their hair goals and hair challenges," Mitchell said. "That's the cool thing with AI -- it has uncovered new data that is helpful for businesses and how to target consumers. And again, just making it personalized."

    Myavana recently raised $5.9 million in seed round funding.

    While the vendor developed proprietary technology, it runs its model on AWS. It also built a conversational AI chatbot with Google.

    Esther Ajao is a TechTarget Editorial news writer and podcast host covering artificial intelligence software and systems. Shaun Sutner is senior news director for TechTarget Editorial's information management team, driving coverage of artificial intelligence, unified communications, analytics and data management technologies. Together, they host the Targeting AI podcast series.

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    43 分
  • Closing the gap between open source and closed AI models
    2024/10/15

    Open source AI models are closing the gap in the debate between open and closed models.

    Since the introduction of Meta Llama generative AI models in February 2023, more enterprises have started to run their AI applications on open source models.

    Cloud providers like Google have also noticed this shift and have accommodated enterprises by introducing models from open source vendors such as Mistral AI and Meta. At the same time, proprietary closed source generative AI models from OpenAI, Anthropic and others continue to attract widespread enterprise interest.

    But the growing popularity of open source and open models has also made way for AI vendors like Together AI that support enterprises using open source models. Together AI runs its own private cloud and provides model fine-tuning and deployment managed services. It also contributes to open source research models and databases.

    "We do believe that the future includes open source AI," said Jamie De Guerre, senior vice president of product at Together AI, on the latest episode of TechTarget's Targeting AI podcast.

    "We think that in the future there will be organizations that do that on top of a closed source model," De Guerre added. "However, there's also going to be a significant number of organizations in the future that deploy their applications on top of an open source model."

    Enterprises use and fine-tune open source models for concrete reasons, according to De Guerre.

    For one, open models offer more privacy controls in their infrastructure, he said. Enterprises also have more flexibility. When organizations customize open source models, the resulting model is something they own.

    "If you think of organizations making a significant investment in generative AI, we think that most of them will want to own their destiny," he said. "They'll want to own that future."

    Enterprises can also choose where to deploy their fine-tuned models.

    However, there are levels involved in what is fully open source and what is just an open model, De Guerre said.

    Open models refers to models from vendors that do not include the training data or the training code used to build the model, but only the weights used.

    "It still provides a lot of value because organizations can download it in their organization, deeply fine-tune it and own any resulting kind of fine-tuned version," De Guerre said. "But the models that go even further to release the training source code, as well as the training data used, really help the open community grow and help the open research around generative AI continue to innovate."

    Esther Ajao is a TechTarget Editorial news writer and podcast host covering artificial intelligence software and systems. Shaun Sutner is senior news director for TechTarget Editorial's information management team, driving coverage of artificial intelligence, unified communications, analytics and data management technologies. Together, they host the Targeting AI podcast series.

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    46 分

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