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☕️ Good morning. It's Friday, July 21. I am happy to share some inspiring trends and news from the AI world, some valuable resources, and a few emerging AI tools. Prepare yourself for the ride! First time reading? join here!
LATEST — Top AI companies, including OpenAI, Alphabet, and Meta Platforms, have made voluntary commitments to the White House to enhance AI safety. They will watermark AI-generated content, test systems before release, and share risk reduction information. The move supports the Biden administration's efforts to regulate AI technology amid its popularity and potential risks. The companies also aim to protect user privacy, eliminate biases, and use AI for scientific problem-solving like medical research and climate change mitigation. here is the link to the article.
🗞️ Today’s Highlights:
EXECUTIVE — The executive’s guide to generative AI: 10 essential truths, 5 unresolved uncertainties – and 1 overarching imperative
AI TOOLS — Insightbase: Ask questions in natural language and get answers in seconds. No more SQL queries, no more data science. Just ask.
IDEAS & QUESTIONS — Study claims ChatGPT is losing capability, but some experts aren’t convinced
LEARNING — Mojo Language: The New Programming Language for 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 — AI-generated movie trailer. Generated by Curious Refuge using Midjourney.
🗞️ EXECUTIVE
Generative AI offers significant opportunities for financial services companies, but it also comes with various risks, both familiar and novel. The use of large datasets for training AI models raises concerns about potential biases that could affect applications if left unaddressed. To tackle these challenges and achieve responsible AI objectives while fulfilling strategic ambitions, five key design principles can guide companies in mitigating risks and fostering a responsible AI environment.
Collaboration between humans and machines is revolutionizing various industries. ChatGPT, a leading model, gained massive popularity and raised concerns about job automation. The Generative AI market is projected to reach USD 900 billion by 2030. It fuels gaming, VR, and conversational AI advancements. Governments and key companies are investing heavily in this transformative technology, driving customer experiences and business growth. However, there are risks to consider, like bias and limited context windows. Companies need to focus on innovative strategies and personalized approaches to stand out in the market.
Generative AI is a powerful technology with transformative potential. It can create new content, automate tasks, and enable personalized experiences. However, leaders must address uncertainties around its impact and navigate evolving regulations. The imperative for executives is to educate themselves and their teams, striking a balance between innovation and responsibility to ride the AI wave successfully.
Generative AI poses several cybersecurity threats, including AI-enhanced malware, AI-infused phishing and social engineering, and AI-powered fraud, which could exacerbate vulnerabilities in SMBs. The economic cost of cyberattacks on SMBs is high, with many businesses unable to operate after experiencing an attack.
Despite the risks, generative AI can reinforce cybersecurity for SMBs by enabling anomaly detection, rapid monitoring, automated response, vulnerability assessment, and patch management. It can help SMBs change the balance between attackers and defenders, particularly for those lacking resources.
A multistakeholder approach involving big technology companies, managed service providers (MSPs), governments, and regulatory bodies is crucial for responsible development and assimilation of generative AI cybersecurity products and services. This collaboration can significantly impact the fight against cybercrime and enhance cybersecurity resiliency for SMBs. The World Economic Forum Partnership against Cybercrime advocates for this collaborative approach.
Ishit Vachhrajani, Global Head of Enterprise Strategy at AWS, discusses leveraging generative AI effectively in enterprises. He emphasizes problem-oriented approaches, strong foundational cloud and data capabilities, responsible AI governance, and skill development. Integration with existing workflows and offering flexibility and choice of models are crucial for success.
🗞️ AI TOOLS
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.
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.
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.
🗞️ IDEAS & QUESTIONS
Researchers from Stanford University and the University of California, Berkeley, released a paper suggesting a decline in GPT-4's performance over a few months. GPT-4's ability to identify prime numbers reportedly dropped dramatically from 97.6% accuracy in March to 2.4% in June. Some experts are skeptical of the findings, attributing the changes to fine-tuning adjustments. OpenAI denies any decrease in GPT-4's capabilities and emphasizes continuous improvement. The lack of transparency in OpenAI's model releases raises concerns, with experts calling for open-source models to address the issue.
In the episode, Peter and Emad discuss AI's impact on journalism and Hollywood, its potential to enhance truthfulness, and the concerns regarding AI-generated content. Emad Mostaque is the CEO of Stability AI, supporting open-source music and image-generating systems.
🗞️ 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.
According to this report, in 2022, North America dominated the market, capturing more than 37% of the total revenue share. Looking ahead, the natural language processing segment is anticipated to experience considerable growth over the forecast period due to advancements in technology and increasing demand. Additionally, the fraud detection segment is expected to exhibit significant growth during the same period, indicating a rising need for robust fraud prevention measures in various industries. These key takeaways highlight the regions and sectors that are likely to have a significant impact on the overall market trajectory in the foreseeable future.
🗞️ LEARNING
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.
🗞️ 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.
Since ChatGPT went viral, concerns have risen about AI taking over human jobs. Experts predict job impacts from AI and other technological advancements, but new roles may also emerge. An HSBC report highlights slower economic growth as a major factor in job displacement, alongside the green transition and tech adoption. While AI is expected to create jobs, humanoid and non-humanoid robots could lead to redundancy. The report emphasizes the need for skilled workers to meet changing demands. Other factors contributing to job losses include supply shortages, rising business costs, higher living costs, and pandemic effects, amid ongoing inflation challenges.
JUST FOR FUN
😂 ChatGPT generated joke of the day.
📺 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.
Source: Curious Refuge
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