Who Are the Developers Working on Generative AI?

☕️ Greetings tech aficionados! It's Thursday, August 31st. Welcome back to our daily exploration of the AI landscape. Together, we'll navigate the latest updates, trends, and insights steering the AI and the business world. Exciting times ahead—let's dive in!

🗞️ Today’s Highlights:

• LATEST NEWS & TRENDS — Who Are the Developers Working on Generative AI Projects?

• INDUSTRY | FUNCTION — How IT teams use Generative AI to make their lives easier

• RESOURCES — The Rise of the AI Engineer

• WORK — Generative AI Can Automate As Many As 75 Million Jobs Globally, ILO Study Finds

• AI TOOLS — Speedwrite: The secret weapon for awesome text. Unique writing, every time.

• CHARTS — Generative AI in Finance and Beyond

🤖 As Generative AI gains prominence, software developers occupy a pivotal role. Insights from a developer survey spotlight North America as a focal point, emphasize the significance of specialized roles like data scientists, and illuminate content preferences. Education's role and AI-assisted tools' uptake shape a narrative of innovation. The upcoming DevGuild: Artificial Intelligence event promises further exploration of this transformative landscape.

Reference: (Who Are the Developers Working on Generative AI Projects?)

🗞️ LATEST NEWS & TRENDS

1️⃣ Generative AI stands to boost U.S. labor productivity by 0.5% to 0.9% annually through 2030, amplifying total productivity growth to 3-4%, a sharp contrast to the 1.4% seen since 2005, according to a McKinsey report. However, successful deployment hinges on comprehensive adoption by stakeholders and workforce adaptability. While freeing up time for higher-value tasks, generative AI is likely to transform job roles, particularly in STEM and office support sectors, but not eliminate them outright.

Source: Tech Republic

2️⃣ In the interplay of global shifts and a century-defining epidemic, the imperative of an open world economy emerges. This calls for steadfast progress, aligning with historical trends and embracing innovation like Artificial Intelligence. As nations interweave destinies, cooperation prevails. Openness fuels advancement; isolation courts obsolescence. The pursuit of a new economic order embodies shared values and humanity's aspirations. Amidst challenges, unity, and open engagement pave the way forward.

Reference: (Artificial Intelligence and the new world order: Economy and peace)

3️⃣ In a world demanding control over human rights data, global communities seek limits for emerging technologies like AI. The absence of federal legislation prompts debates in the US and EU. Striking a balance is key. Boundaries mean regulation and two approaches emerge: risk-based self-regulation or integrating human rights throughout AI's lifecycle. Urgent action is vital as AI's impact is evident now. Addressing bias, transparency, and governance gaps is paramount. Human rights must guide AI's potential and risks.

Reference: (Anthropomorphising the Digital Society: Artificial Intelligence Determinants and Human Rights)

4️⃣ AI is disrupting societal norms, prompting regulatory scrutiny. Venture capital pours into generative AI, driven by cross-industry convergence. Regulation, a critical dialogue, bridges technologists' innovation, and regulators' consumer protection concerns. Historical parallels, like internet oversight, offer lessons. Certifications akin to SSL/TLS can secure AI while fostering growth.

Reference: (We don’t have to reinvent the wheel to regulate AI responsibly)

5️⃣ A report by the Council of Europe delves into the relationship between AI and education, emphasizing human rights, democracy, and the rule of law. It critically examines AI's impact on learning and teaching, highlighting challenges like pedagogy, surveillance, and ethics. It envisions an AI-powered education landscape that upholds core values for the common good.

Reference: (ARTIFICIAL INTELLIGENCE AND EDUCATION A critical view through the lens of human rights, democracy and the rule of law)

🗞️ INDUSTRY | FUNCTION

Generative AI is redefining creative content production, powered by a robust behind-the-scenes infrastructure. Key elements include hardware acceleration through GPUs and TPUs for faster computation and cloud-based solutions like AWS and Azure for scalability and cost-effectiveness. Distributed computing frameworks and effective data pipelines are equally vital. Monitoring tools like Prometheus and ethical practices ensure performance and responsible use. As generative AI's scope expands, so does the need for innovative and ethical infrastructure management.

Reference: (The Evolving Landscape of Generative AI Infrastructure)

Generative AI platforms are revolutionizing the workflow across various professions, from software engineering to cybersecurity. With impressive adoption rates, these tools significantly cut down time spent on tasks like code writing and data review. However, they pose security risks, such as aiding bad actors in cracking passwords or enhancing phishing tactics. While there's a surge in "shadow IT" practices—employees using these tools without employer knowledge—the necessity for organizational guidelines is increasingly evident. They offer unparalleled productivity gains but require careful and ethical application.

Reference: (How IT teams use Generative AI to make their lives easier)

🗞️ RESOURCES

The surge in accessible AI, primarily through APIs and Foundation Models, has democratized AI applications, making what used to take years now doable in an afternoon. The landscape is awash with tools and models for AI Engineers to employ. These professionals, often distinct from traditional ML engineers, are becoming pivotal figures in leveraging AI for product development. They operate across sectors and are poised to be the most sought-after roles of the decade.

Reference: (The Rise of the AI Engineer)

🗞️ WORK

Artificial Intelligence's infiltration into various aspects of life prompts concerns over job displacement. The International Labor Organization (ILO) highlights that AI could affect 75 million jobs globally, potentially replacing human roles. On a brighter note, AI could augment 427 million jobs, enhancing work quality and efficiency. Notably, the impact is gender-biased, putting 21 million women at higher risk of automation, mainly in clerical roles. While low-income countries face lesser risks, high-income regions are more vulnerable, unless proactive skill development occurs to mitigate the negative effects.

Reference: (Generative AI Can Automate As Many As 75 Million Jobs Globally, ILO Study Finds)

🗞️ AI TOOLS

Octocom: The best AI chatbot for your Ecommerce store.

Postwise AI: Craft engaging posts with AI, schedule effortlessly, and watch your followers grow

Photo AI: Create stunning selfies with AI - no camera

Speedwrite: The secret weapon for awesome text. Unique writing, every time.

Aragon AI: Transform your Selfies into AI-Generated Headshots

25 Best Generative AI Tools: The Power and Pressure Game Is On

Source: RapidOps 

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.

🗞️ CHARTS

 👀 Generative AI in Finance

Financial firms are actively collaborating with tech giants like OpenAI and Nvidia to integrate AI into multiple functions, such as risk management and financial education. Companies like Stripe and Morgan Stanley are among those utilizing OpenAI's GPT-4. On the consumer front, Klarna employs ChatGPT for personalized shopping recommendations, initially in North America. Meanwhile, Brex and Alaan focus on real-time corporate spending analytics, and OnFinance, Plum, and Douugh employ ChatGPT to foster financial literacy.

Source: WhiteSight 

 👀 The New Language Model Stack

Reviewing 33 companies across the Sequoia network, there is a significant shift towards integrating large language models (LLMs) into various product ecosystems. With a 65% uptick in production applications in just two months, these LLMs are revolutionizing areas from code completion to consumer payments. The technology stack is evolving, emphasizing LLM APIs, retrieval mechanisms, and orchestration frameworks. Concerns around trustworthiness, data privacy, and output quality are paramount. Yet, the consensus is clear: LLMs are the future of AI-driven applications.

Source: Sequoia Capital

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

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_{I'm not a newsletter expert so you might find my approach a tad different. In my daily dives into the world of AI, I handpick the latest gems, initially to support the AI projects that I’m working on. Realizing that these snippets might resonate with others, I thought, "Why not share this with my community and fellow AI enthusiasts?" I truly want this newsletter to be valuable to you so if there's anything on your mind—praises, critiques, or just a hello—please drop me a note. You can hit reply or shoot me a message directly at my email address: [email protected].}