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Most commonly reported uses of Generative AI tools
🗞️ The Tech Issue | August 1, 2023
Qamar Zia
August 01, 2023
☕️ Good morning. It's Tuesday, August 1. I've got some awesome updates to share with you today. Brace yourself for the coolest AI trends, valuable insights, resources, and mind-blowing cutting-edge tools. Get ready to be amazed! First time reading? join here! If you like my newsletter, please share it with your team. It will help me immensely.
The McKinsey Global Survey shows rapid adoption of generative AI tools, with one-third of organizations already using them. Respondents expect significant disruption in their industries and plan to invest more in AI. However, many organizations are not adequately addressing the risks, and overall AI adoption remains steady. Leading companies, AI high performers, are ahead in adopting AI and using gen AI for revenue generation. Workforce reskilling is expected to be substantial due to AI adoption. Here is a must-read report from McKinsey & Co released this morning which includes the most commonly reported uses of generative AI tools in marketing and sales, product and service development, and service operations.
🗞️ Today’s Highlights:
EXECUTIVE — 20 issues shaping generative AI strategies today
IDEAS & QUESTIONS — How generative AI fits into content development processes
LEARNING — 10 Generative AI Tools for Developers to Unlock New Possibilities
AI TOOLS — Scale: Make the best models with the best data. Scale Data Engine leverages your enterprise data, and with Scale Generative AI Platform, safely unlocks the value of AI.
INDUSTRY & FUNCTIONS — Retailers Take Note: Generative AI is Killing the Single Voice of the Brand
WORK — Preparing your workforce for generative AI
JUST FOR FUN — Barbenheimer Movie Trailer. AI-generated using Midjourney by Curious Refuge.
🗞️ EXECUTIVE
CIOs are at the forefront of the rapid adoption of generative AI (gen AI) in organizations since the launch of ChatGPT in November 2022. They face multiple challenges, including deciding whether to allow or limit gen AI use, managing evolving risks, establishing acceptable use policies, and addressing data privacy and security concerns. CIOs must also prioritize use cases, make buy vs. build decisions, ensure enterprise readiness, and implement quality assurance procedures. As gen AI disrupts business models, CIOs play a crucial role in leading organizational change and upskilling employees to work effectively with this technology. Collaboration with the executive team is essential to navigate the opportunities and challenges presented by gen AI. This article discusses 20 key points in detail.
Generative AI is a hot topic among companies during the second-quarter 2023 earnings season. Many have filed SEC documents mentioning "generative AI," while major tech companies collaborate to set industry standards. However, the rapid expansion of generative AI tools raises questions about data safety for consumers. Companies like Meta, Microsoft, Alphabet, Snap, Adobe, and Omnicom are actively using generative AI in various aspects of their businesses, but they also acknowledge potential risks and ethical considerations.
China is embracing and regulating generative AI for economic growth. Chinese Big Tech firms have launched their LLM applications to compete with ChatGPT. China will implement the world's first rules on generative AI. Beijing hosts half of all China-developed AI models. Tencent, Huawei, Baidu, and Alibaba have introduced LLM services for various industries. The US is also working on regulating AI tools like ChatGPT.
Video source: Techwireasia.com
🗞️ IDEAS & QUESTIONS
This article discusses the concept of Generative AI and its potential impact on content development. It distinguishes between two approaches to content generation: augmented generation, where AI assists humans in creating content, and automated generation, where AI takes full responsibility for content creation. The article compares these approaches to levels of automation in self-driving cars.
The article emphasizes that Generative AI should provide content teams with control over the content creation process and suggests considering practicality when implementing automation. It highlights that automated content generation works best for routine and predictable tasks, while augmented content generation involving human collaboration is suitable for more complex and creative endeavors.
The text explores the strengths and limitations of AI and human content creators in various aspects, such as wording precision, originality, accuracy, and volume of content generation. It concludes that the right approach to adopting Generative AI will depend on the specific use case and the balance between AI assistance and human involvement in content development. The article encourages iterative exploration and careful consideration of AI's value in enhancing content creation processes.
🗞️ LEARNING
Generative AI has transformed development by offering powerful tools to create original content without relying on existing data. It plays a vital role in enhancing creativity, automating tasks, and inspiring artists and designers. The top generative AI tools include Chatsonic, Jasper Chat, Chat by Copy.ai, ChatFlash by Neuroflash AI, GrowthBar, Rytr Chat, Botsonic by Writesonic, ChatGPT (OpenAI), Easy Peasy AI Chat, and LaMDA (Google). When choosing a tool, developers should consider their needs, evaluate capabilities, and be mindful of ethical considerations. Generative AI's future holds potential for advanced specialized tools and integration with other technologies.
Mojo language shows promise as a fast and Python-compatible language tailored for AI/ML. However, it is unlikely to completely replace Python in the near future due to Python's massive ecosystem, community, and established presence in data science and ML. At best, Mojo may become a complementary language to Python, especially when speed is crucial.
Thi tutorial provided a review of the features and syntax of Mojo programming language, including code examples. It also compares Mojo with Python, considering aspects like performance, syntax, functionality, and compatibility.
"The Prompt" presents technical insights into generative AI, focusing on new development approaches, scalability, and cost optimization. The process involves pre-training large models, adapting them with task-specific prompts, and considering information retrieval techniques. To optimize cost, hardware accelerators like GPUs and TPUs are recommended. As generative AI matures, MLOps practices evolve. Business leaders should assess ROI, consider model development options, and adapt to the rapidly evolving field. Google Cloud offers an enterprise-ready generative AI platform for businesses.
🗞️ AI TOOLS
Trinka: Trinka is an online grammar checker and language correction AI tool for academic and technical writing.
Scale: Make the best models with the best data. Scale Data Engine leverages your enterprise data, and with Scale Generative AI Platform, safely unlocks the value of AI.
Insightbase: Ask questions in natural language and get answers in seconds. No more SQL queries, no more data science. Just ask.
Notion: Access the limitless power of AI, right inside Notion. Work faster. Write better. Think bigger.
Namelix: Generate a short, brandable business name using artificial intelligence
Disclaimer: 1) The tool descriptions may include messaging from each tool site. 2) Please thoroughly read the site details before using and/or acquiring any of the tools listed above.
🗞️ INDUSTRY & FUNCTION
Generative AI is revolutionizing retail marketing by enabling brands to have multiple personalized voices for individual customers, enhancing communication and shopping experiences. Brands that quickly adapt to this technology will gain a competitive edge, while those who don't may be left behind. Generative AI is a game-changer in the retail industry, providing dynamic and individualized communication at scale.
Generative AI Companies With >$5MM Raised (as of March 2023)
Source: Pitchbook, Crunchbase, public sources
Produced by: Kelvin Mu
🗞️ WORK
Generative AI is evolving rapidly, and organizations must define its usage and prepare their workforce accordingly. While it shows promise, there are risks such as exposing confidential data and bias. Developing clear policies, educating employees, understanding regulatory impact, safeguarding data, testing for bias, and upskilling the workforce is crucial. KPMG's eight core principles guide responsible AI implementation.
🗞️ JUST FOR FUN
📺 Barbenheimer Movie Trailer. AI-generated using Midjourney by Curious Refuge.
It's only a matter of time before AI-generated videos go from being near-realistic to realistic.
Video source: Curious Refuge
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