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AWS's 3 Gen AI Use Cases
🗞️ The Tech Issue | September 29, 2023
☕️ Happy Friday, September 29th. Welcome to the Friday edition.
!? AWS is significantly investing in Large Language Models (LLMs) to enhance its Amazon Connect platform, particularly in contact centers. Dave Lemons of AWS highlighted three core use cases: augmenting agent-assist, bolstering manager-assist, and enriching customer self-service experiences. Emphasizing security, accuracy, and reduced bias, AWS aims to elevate trust and value in generative AI outcomes. The integration of GenAI notably accelerates response times in agent-assist scenarios, offers concise summarizations and insightful analytics for managers, and broadens the capabilities of self-service solutions. AWS envisions GenAI's further potential in automating knowledge article creation and identifying customer service automation opportunities, mirroring moves by Salesforce and Five9.
🗞️ Today’s Highlights:
LATEST NEWS & TRENDS — How some creators are using AI to make higher quality content – faster – for platforms
INDUSTRY | FUNCTION — Been there, doing that: How corporate and investment banks are tackling Gen AI
RESOURCES — Introducing New AI Experiences Across Our Family of Apps and Devices
WORK — Learn AI now or risk losing your job, experts warn
AI TOOLS — DataTera: Solution to convert any files or websites to the CRM in seconds.
CHARTS — AI and science: what 1,600 researchers think
🗞️ LATEST NEWS & TRENDS
1️⃣ Generative AI tools are aiding content creators and brands like Coca-Cola in enhancing creativity and productivity. Platforms such as YouTube are launching AI-powered features, notably "Dream Screen," to aid in content generation, while Snap scales down its AR department due to generative AI's rise. This technology is becoming integral in marketing strategies, helping in efficient campaign management and content diversification. Yet, challenges like data privacy laws and the immature state of generative AI, requiring human oversight for quality, are notable.
2️⃣ Generative AI, blending human creativity and technology, reshapes problem-solving and content creation across art, literature, and music, propelling businesses into novel explorations. While businesses exhibit mixed reactions - enthusiasm, experimentation, and caution, successful integration necessitates strategic insight addressing organizational challenges. Key steps include ensuring data readiness, fortifying infrastructure, nurturing a skilled team, fostering innovation, and establishing robust governance frameworks. These principles, grounded in real-world examples, aim to bridge the gap between the potential and actual deployment of generative AI, urging enterprises to not merely adapt, but lead in this technological frontier.
3️⃣ Big Tech firms Google, Amazon, and Microsoft unveiled plans to integrate generative AI into their products, aiming to enhance user experiences. Despite past lukewarm receptions to digital assistants, these companies are optimistic. Microsoft's substantial investment in generative AI, through its Copilot assistant, demonstrates a determined push towards AI-powered digital aid. However, the public's hesitance, coupled with previous missteps of AI tools, hints at a cautious path ahead before such technologies seamlessly blend into our daily routines.
4️⃣ Google is extending its AI-driven Search Generative Experience (SGE) to US teens (13-17) for a conversational search interface, alongside new features enhancing context and refining AI training against false or offensive queries. With safety measures to block inappropriate content, this expansion follows SGE's popularity among younger users. Additionally, an "About this result" notice will elucidate the AI's response generation, aiding understanding of the technology while aiming for improved accuracy and quality in addressing sensitive or false premises in queries.
5️⃣ Amazon has launched Bedrock, a generative AI service offering models from Amazon and third-party partners. Bedrock enables AWS customers to create AI applications and agents for various tasks. It will soon include Meta's Llama 2 model. While similar to Google's Vertex AI, Bedrock integrates seamlessly with AWS services, potentially offering advantages. This move reflects the growing interest in generative AI, making it accessible to businesses and employees. Amazon also introduced the Titan Embeddings model for multilingual text conversion.
🗞️ INDUSTRY | FUNCTION
Generative AI (gen AI) is poised to add substantial value to Corporate and Investment Banks (CIB) by enhancing productivity and operations across new product development, customer operations, and marketing and sales. While leading banks are advancing in gen AI adoption, others face challenges like computing costs or intellectual property constraints. Gen AI, extending capabilities in natural language understanding, can automate various tasks, from compliance report analysis to client service document creation, potentially adding between $200 billion and $340 billion in value across the banking sector.
🗞️ RESOURCES
Meta is launching AI features across its platforms, introducing Meta AI, a conversational assistant, alongside 28 other unique AIs, some embodied by cultural icons. New AI tools facilitate creative image editing and sticker generation, enhancing user expression and interaction. Meta also unveiled AI Studio for external AI development, aiming to extend these AI services to businesses and creators, thus fostering a burgeoning ecosystem of AI-driven communication, creativity, and connectivity within its app universe.
🗞️ WORK
Adoption of AI across sectors is accelerating, markedly showcased at St. Michael's Hospital, Toronto. Dr. Mamdani emphasizes that AI adoption among clinicians is imperative to remain relevant. With AI handling significant workloads, employees across fields are urged to embrace AI or face potential job obsolescence. Experts like Armine Yalnizyan stress the importance of adapting to and learning this transformative technology, as it's rapidly changing the job landscape and how work is conducted across industries.
Reference/Source: (Learn AI now or risk losing your job, experts warn)
🗞️ AI TOOLS
🔧 DataTera: Solution to convert any files or websites to the CRM in seconds.
🔧 HeartSpace: Get your message out and contribute to a more constructive and solution-oriented media climate with the power of AI.
🔧 Diddo: Elevate your website's user experience by integrating Diddo, a ChatGPT-powered chatbot that's as unique as your business. Say goodbye to generic interactions and hello to personalized, intelligent conversations.
🔧 ArtiscribeAI: Craft captivating descriptions, captions, and art effortlessly with the world’s first app designed exclusively to empower artists
🔧 Vespio: Increase your win rate & revenue with Vespio’s AI Powered Sentiment Analysis tool by catching hidden customer desires from every conversation.
Disclaimer: 1) The tool descriptions are from the company behind each tool/app. 2) Please read the site details thoroughly before using and/or acquiring any of the tools listed above. We have not tested these tools and we will not be liable for anything.
🗞️ CHARTS
👀 Artificial Intelligence is steadily embedding itself in scientific research, as a recent Nature survey of over 1,600 scientists demonstrates. A majority believe AI tools will be 'very important' or 'essential' in the next decade for data processing and other computational tasks. However, there's a disconcerting flip side—concerns over AI exacerbating biases, enabling fraud, and rendering research non-reproducible. The dual perspectives echo the broader discourse, highlighting AI's potent influence while cautioning against unintended ethical and methodological pitfalls.
Reference/Source: Nature (AI and science: what 1,600 researchers think)
Disclaimer: The audio-visual content is courtesy of the source provided above.
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