AI Giants are Losing Money

☕️ Greetings! It's Tuesday, October 10th. Welcome back to my daily dive into the AI landscape.

♨️ Microsoft's aggressive price hikes on its AI-enabled Microsoft 365 suite spotlight the financial challenges of scaling generative AI. Unlike traditional machine learning models, generative AI demands exponentially more computational power, inflating operational costs. Industry experts argue that despite these cost-intensive ventures, tech behemoths are heavily subsidizing AI services, likely incurring losses. However, the long-term perspective sees costs eventually diminishing, with the technology becoming increasingly integral to staying competitive. The key to profitable AI lies in its practical application, particularly in enhancing the productivity of specialized professionals. The current generic, resource-intensive models may not be feasible for most organizations, paving the way for more efficient, customizable solutions. Read more here.

🗞️ Today’s Highlights:

• LATEST NEWS & TRENDS — Gen Z is Defining the Future of Work – on Their Own Terms, Reveals Morning Consult & Samsung Survey

• INDUSTRY | FUNCTION — Generative AI and machine learning are engineering the future in these 9 disciplines

• RESOURCES — Securing Generative AI: An Introduction to the Generative AI Security Scoping Matrix

• ENTREPRENEURSHIP — Meet some of the Gen Z entrepreneurs behind the next AI innovation wave

• AI TOOLS — Talently AI: Your AI Interviewer.

• CHARTS — The Foundation Model Transparency Index

🗞️ LATEST NEWS & TRENDS

1️⃣ Gen Z is steering the future of work with a keen focus on aligning careers with their passions. A survey by Morning Consult and Samsung Solve for Tomorrow found 21% of Gen Z see AI as creating job opportunities, while 40% foresee AI-driven job disruptions. A significant 50% aspire to entrepreneurship, emphasizing their innovative and autonomous nature. Industries like Entertainment and Media, Technology, and Health draw their interest. The study also highlighted Gen Z's value on work-life balance, skill development, and adaptability. Their entrepreneurial spirit is being recognized with new awards in STEM competitions, supporting their journey in shaping tomorrow's workforce.

Reference: (Gen Z is Defining the Future of Work – on Their Own Terms, Reveals Morning Consult & Samsung Survey)

2️⃣ Stanford HAI's recent transparency index reveals a glaring lack of disclosure from top AI model creators like OpenAI and Meta, particularly concerning societal ramifications. The index assessed 10 leading AI systems on 100 different transparency criteria, examining how they're built, function, and are utilized. Meta’s Llama 2 led the pack with a 54% transparency score, trailed by BloomZ and OpenAI's GPT-4. Even though OpenAI collaborates with numerous companies, it was notably tight-lipped about its own research and data origins. Remarkably, none of the analyzed companies offered details on the societal impact of their models, such as dealing with privacy or bias, underscoring the need for regulation and oversight.

Reference: (The world’s biggest AI models aren’t very transparent, Stanford study says)

3️⃣ Generative AI has evolved from academic curiosity to a significant business catalyst, with its influence expected to surge in the coming years. Business leaders overwhelmingly acknowledge its importance, but practical implementation lags, partly because current large language models (LLMs) lack specificity and can produce inaccurate "hallucinations." The solution lies in Retrieval Augmented Generation (RAG), a technique that uses additional data sets to refine LLM responses. RAG enhances accuracy by comparing user prompts to a database of vectorized data, offering more contextual and reliable outcomes. Leveraging this method helps companies to transform generative AI's latent potential into actual gains, sidestepping issues like hallucinations and data staleness.

Reference: (RAG to riches: how to implement better GenAI in business)

4️⃣ McKinsey & Company expressed strong optimism for generative AI's transformative potential across various industries, rebuffing doubts cast by the failures of Amazon’s hiring tool and IBM Watson. Speaking at an event in Seoul, senior partners Lareina Yee and Vinayak HV acknowledged the technology's potential pitfalls, such as job displacement in knowledge sectors and intellectual property risks. However, they emphasized its benefits, including enhanced worker happiness and productivity. Yee, formerly McKinsey's chief diversity officer, also differentiated generative AI from Amazon’s analytical AI, highlighting its ability to improve recruiting processes without bias. Jeff Galvin, another senior partner, projected that generative AI could unlock $4.4 trillion in global economic value annually.

Reference: (McKinsey expects GenAI to bring 'less toil, more joy')

5️⃣ The recent rise of generative AI has ignited a captivating rivalry between proprietary and open-source models, each with its own set of merits. The launch of OpenAI's GPT-4 and the buzzworthy "Woodstock of AI" event epitomize this dichotomy. Proprietary models, represented by giants like OpenAI, lead in capability and are considered safer. Open-source models, celebrated at events like Woodstock of AI, promote a collaborative ecosystem and are gaining traction for their adaptability and transparency. This tug-of-war is shaping the future of AI, influencing everything from business applications to ethical considerations. The landscape seems set for a healthy coexistence, offering the best of both worlds.

Reference: (Achieving Balance in Generative AI: Open-Source Versus Proprietary Models)

🗞️ INDUSTRY | FUNCTION

Generative AI is emerging as a game-changer across multiple engineering fields, offering unprecedented efficiency and precision. The technology excels in tasks ranging from automating code in software engineering to optimizing material use in mechanical engineering. It's also making strides in data engineering, providing actionable insights, and in civil engineering, enhancing infrastructure design. Further applications extend to electrical engineering for circuit design, chemical engineering for process optimization, biomedical engineering for accelerated drug discovery, aerospace engineering for aircraft design, and environmental engineering for waste management. As a versatile optimizer, generative AI is setting new benchmarks, urging engineering leaders to adapt and stay ahead.

Reference: (Generative AI and machine learning are engineering the future in these 9 disciplines)

🗞️ RESOURCES

Generative AI brings new challenges in cybersecurity. Amazon Web Services (AWS) advises organizations to consider security and governance issues based on the type of generative AI they are deploying. They introduce a Generative AI Security Scoping Matrix to help identify key security disciplines based on ownership levels, from consumer apps to self-trained models. The post also covers issues in governance, risk management, controls, and resilience, emphasizing the need to adapt existing cybersecurity best practices to the unique threats posed by generative AI.

Reference: (Securing Generative AI: An introduction to the Generative AI Security Scoping Matrix)

🗞️ ENTREPRENEURSHIP

Gen Z entrepreneurs are not just spectators in the AI revolution; they are front and center, shaping its future. In San Francisco, young visionaries, often leaving big tech or academia behind, join a unique 12-week AI accelerator program, Hacker Fellowship Zero. Here, they get housing, investment, and resources to bring their startups to life. In New York, similar tech houses are becoming incubators for AI innovations. These Gen Zers range from full-time entrepreneurs like Iddris Sandu, founder of Spatial Labs, to side-hustlers like Coco Chen, who created an AI dream interpretation app. They're not just focused on leveraging AI for profit but are also keen on its ethical and responsible use. Their collective efforts are making them an influential force in the AI sector.

Reference: (Meet some of the Gen Z entrepreneurs behind the next AI innovation wave)

🗞️ AI TOOLS

🧰 Talently AI: Your AI Interviewer.

🧰 QuestGen AI: Generate quizzes from any text in one click using AI.

🧰 Reclaim AI: Personal time tracking app for tasks, habits, & meetings.

🧰 BrainTrustData: Rapidly ship AI without guesswork.

🧰 Adept AI: A new way to use computers. Building a machine learning model that can interact with everything on your computer.

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

 👀 Stanford HAI's recent transparency index reveals a glaring lack of disclosure from top AI model creators like OpenAI and Meta, particularly concerning societal ramifications. The index assessed 10 leading AI systems on 100 different transparency criteria, examining how they're built, function, and are utilized. Meta’s Llama 2 led the pack with a 54% transparency score, trailed by BloomZ and OpenAI's GPT-4. Even though OpenAI collaborates with numerous companies, it was notably tight-lipped about its own research and data origins. Remarkably, none of the analyzed companies offered details on the societal impact of their models, such as dealing with privacy or bias, underscoring the need for regulation and oversight.

Reference/Source: Stanford University (The Foundation Model Transparency Index)

Disclaimer: The audio-visual content is courtesy of the source provided above.

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