How AI Universal Search is Transforming Knowledge-based Work
PLUS: A new AI email tool that saves users time on sending messages
Today we cover how knowledge-based work is being made more efficient through AI integration and universal search tools.
We also highlight an AI tool that automates the email process, allowing users to save time on crafting personalized responses and suggesting meetings.
Let’s get to it!
💡 1 USE CASE
How AI Universal Search is Transforming Knowledge-based Work
Knowledge-based work is being profoundly enhanced by advances in artificial intelligence. AI systems are becoming more sophisticated at automating rote tasks & generating insights from data. Through this automation, AI is elevating knowledge workers' productivity and value.
The nature of work has fundamentally changed in the wake of remote and hybrid work trends. Employees now face distractions and fractured workflows across countless apps and browser tabs. In a recent Economist Impact study by Dropbox, knowledge workers reported losing over 500 hours per year to distractions.
To address these challenges, Dropbox is leveraging artificial intelligence to design and power the next generation of knowledge work.
Dropbox's new AI-powered products like Dash and Dropbox AI connects apps, tools, and content through universal search, while Dropbox AI summarizes files and answers questions across entire accounts.
One major benefit of universal AI search is its ability to rapidly analyze massive datasets to uncover patterns and trends. For example, lawyers can use AI legal research tools to quickly sift through case law. Financial analysts leverage AI to model risks and forecast market movements. AI-powered tools are becoming integral to knowledge discovery across many domains.
However, to fully enhance their work through AI, knowledge workers must hone new skills. This includes learning to collaborate with AI systems to effectively evaluate their recommendations, and apply ethics principles to guide their use. With prudent governance and training, humans and AI can form extraordinarily productive partnerships.
Three examples of how AI can enhance knowledge work:
Automated research - Knowledge workers use AI to uncover articles, data, & experts to enhance research and analysis. Streamlining discovery and improving ideation efficiency.
AI-assisted coding Programmers use AI coding tools to generate code, debug errors, and suggest syntax. Overall speeding up the software development process.
Automated data entry - AI extracts and structures information from forms and documents into databases. Eliminating tedious manual data entry.
🛠️ 2 TOOLS
Ready to Send (🔗 link)
Ready to Send is a tool that auto-generates email drafts, trained in the tone & voice of its user. Automating the email process is a way to save users time on monotonous replies. The application cuts down on the amount of time spent crafting messages and can even send out Calendly links or suggest meetings.
Meetingflow (🔗 link)
Meetingflow helps optimize the customer meeting process for enterprise users. This tool aims to improve meetings that went poorly and simplify aspects of preparing for a meeting. It can automatically update your CRM and dictate and organize your notes.
🥽 3 TRENDS
AI advancements help Meta bring dexterous robotics closer to reality (🔗 link)
Meta and Nvidia researchers have made strides in embodied AI, teaching virtual agents skills that could aid real-world robot dexterity. Meta created 3D simulations where AI agents collaborate with human avatars on household tasks, learning to work fluidly with people.
Nvidia's EUREKA system automatically generates code to teach virtual agents difficult motor skills like pen twirling. They specifically trained the models in simulated environments allowing for quick iteration. EUREKA iteratively improves the code, helping the agents generalize learning to new tasks.
Using simulated environments allows the AI agents to practice complex physical skills faster than other automated systems and robots The research lays the groundwork for integrating embodied AI into future real-world robotics, showing promise for human-robot collaboration.
Microsoft study finds risk of harmful text generation higher in Large Language Model GPT-4 (🔗 link)
Researchers affiliated with Microsoft found GPT-4 more prone than predecessor GPT-3.5 to generating toxic, biased text when prompted with malicious instructions.
Carefully constructed "jailbreaking" prompts led GPT-4 to produce more harmful text versus GPT-3.5. Researchers speculate GPT-4's increased vulnerability arises from closely following human instructions.
Microsoft ensured products were not impacted, and shared findings with GPT-4 creator, OpenAI.
Google Search rolls out feature for English learners to practice speaking (🔗 link)
Google recently introduced an English-speaking practice feature on Google Search for Android users in select countries. Learners get personalized prompts to verbally respond to real-life situations. They receive instant feedback analyzing semantics, grammar, and pronunciation.
Other key features:
Ability to tap words for in-context translations to understand meanings.
Technology advances like deep learning models enable accurate error correction and complexity estimation.
Designed to supplement other learning resources and increase speaking confidence.
Currently aimed at English learners with plans to expand language and country availability.
Innovations like deep learning models and contextual word translations aid the experience. Designed to supplement other resources, it aims to boost confidence in conversational English. Google plans expanded language and country availability.
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The Simply Augmented Team