Among other things…
This Week in AI: Accelerationism, AGI and the Law
… Thomson Reuters on Wednesday (Nov. 15) launched a series of initiatives aimed at transforming the legal profession through the use of generative AI.
This comes as PYMNTS Intelligence in “The Confluence of Law and AI: An Inevitability Waiting to Happen,” a collaboration with AI-ID, finds that more than half of legal professionals are uncertain about the technology’s reliability, and nearly two in five do not trust it.
Consumers of legal services are not entirely won over either, with 55% of clients and potential clients expressing serious concerns about the use of AI within the legal profession.
Still, 62% of legal professionals believe that effective use of generative AI will differentiate successful firms from unsuccessful ones in as little as five years. An even higher share, 80%, agree that generative AI will introduce “transformative efficiencies” — a sentiment echoed by law firms and corporate legal departments.
Those potential benefits — transformative across not just law but all sectors — are a part of why Chinese tech giant Alibaba reportedly said Thursday it will not spin off its cloud intelligence business amid the ongoing focus on AI.
A new tool for open source intelligence in general.
https://hbr.org/2023/11/use-genai-to-uncover-new-insights-into-your-competitors
Use GenAI to Uncover New Insights into Your Competitors
… This real example illustrates companies’ growing problem of information overload regarding markets and competitors, which often prevents the C-suite from making the best decisions available given the data at its disposal. Financial Times Stock Exchange 100 Index companies’ reports run, on average, more than 223 pages and contain in excess of 147,000 words — and are growing by almost nine pages a year. It is hardly surprising that company experts responsible for analyzing competitive information — in marketing intelligence, strategy, strategic management accounting (a common business function in European companies), etc. — only focus on the sections that are apparently relevant to their function, often missing genuinely relevant information in the rest of the document.
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