Do Humans want AI to be Superintelligent?

☕️ Greetings AI enthusiasts! It's Wednesday, September 20th. Welcome back to our daily dive into the AI landscape. We'll navigate the latest updates, trends, and insights from the AI and the business world. Let's begin!

!? In a revealing moment of public skepticism, a majority of Americans are giving a thumbs-down 👎👎🏾👎🏽👎🏼👎🏻 to the utopian dreams of superintelligent AI. A poll conducted by YouGov and commissioned by the AI Policy Institute underscores this sentiment, with 63% favoring regulations to actively curb the development of AI that surpasses human intelligence. So, why are tech behemoths like OpenAI intent on spawning artificial general intelligence (AGI) without our collective nod? While we squabble over the "how" of control, we've sidestepped the more pivotal "should we even" question. Meanwhile, the elite's tech-driven discourse forges ahead, often sidelining what the general populace genuinely desires or fears, casting shadows over the very democracy they claim to enrich.

Reference: Vox (AI that’s smarter than humans? Americans say a firm “no thank you.”)

Image source: theaipi.org

🗞️ Today’s Highlights:

• LATEST NEWS & TRENDS — Journey from beach bum to NASA innovator, the standout catalyst is generative AI engineering.

• INDUSTRY | FUNCTION — How to Infuse AI Into Your Current Sales and Marketing Processes

• RESOURCES — IBM Commits to Training 2 Million in AI to Address Skills Gap

• WORK — Australia Is Adapting Fast to a Generative AI World

• AI TOOLS — Land in the Inbox. Not the Spam Folder. Maximize Email Deliverability

• CHARTS — The data dividend: Fueling generative AI

🗞️ LATEST NEWS & TRENDS

1️⃣ In Ryan McClelland's transformative journey from beach bum to NASA innovator, the standout catalyst is generative AI engineering. It's not just a tool for him; it's an extension of his imaginative ingenuity. Using Autodesk’s Fusion 360 software, McClelland instructs AI to conceptualize new spacecraft parts, and what emerges are eccentric yet efficient designs. These AI-crafted components are lighter and stronger, fulfilling the crucial criteria of space travel. As this tech gains traction, we're witnessing the dawn of an era where AI doesn't merely assist but pioneers alongside humans in crafting the future of space exploration.

Reference: (Ryan McClelland is pushing NASA into the next space era with generative AI)

2️⃣ MIT has kicked off an intellectually charged initiative, led by President Sally Kornbluth and Provost Cynthia Barnhart, to decode the societal impacts of generative AI. They invited proposals and received a plethora of ideas across diverse fields, including climate change, healthcare, and the arts. A hefty $50,000-$70,000 grant will fuel each of the 27 chosen research ventures. These seminal papers will act as lodestars, exploring both the promise and the pitfalls of generative AI. What's next? I'd keep my eyes on these papers—they're bound to recalibrate our collective outlook on AI's role in our lives.

Reference: (MIT scholars awarded seed grants to probe the social implications of generative AI)

3️⃣ Apple's recent event made waves not just for its eco-friendly watch but also for spotlighting its in-device "neural engine." This technology fundamentally diverges from the cloud-based AI models of competitors, emphasizing privacy and low latency. The company is also reportedly outdoing OpenAI's large language models, positioning Apple as an under-the-radar force in the AI landscape. Meanwhile, Fast Company reveals influencers in AI, and major tech firms, despite ethical concerns, pledge to uphold White House AI standards. It's a complex, rapidly evolving tapestry of promise and peril in AI's trajectory.

Reference: (We just got another glimpse at Apple’s AI ambitions)

4️⃣ In a curious legal twist, Pulitzer-winning novelist Michael Chabon and other high-caliber writers are locking horns with OpenAI over alleged copyright infringement. The suit argues that OpenAI's ChatGPT is trained on copyrighted materials, thus crossing legal boundaries. Notably, the authors point fingers at datasets labeled 'Books1' and 'Books2,' speculating they may have been sourced from Project Gutenberg or even 'shadow libraries' that host pirated content. This potentially landmark case could redefine the boundaries of AI ethics and copyright law, a subject currently under scrutiny by the US Copyright Office.

Reference: (Pulitzer Prize winning author Michael Chabon and others sue OpenAI)

5️⃣ ChatGPT Enterprise just rolled onto the stage, and it's the answer to corporate prayers for AI-driven communication. Forget what you knew about its consumer counterpart—this version amplifies features and hardens security. Tailored to meet business needs, it's about to infiltrate offices globally, converting the skeptics. With this launch, OpenAI shifts from a casual conversation facilitator to a critical business infrastructure element. It's not just an upgrade; it's a game-changer for Fortune 500 companies down to garage startups. Welcome to a new era of enterprise AI interaction.

Reference: (What is ChatGPT Enterprise? Business-focused Generative AI)

🗞️ INDUSTRY | FUNCTION

Ah, the allure of the "next big thing." After the less-than-stellar adoption rates of VR and crypto in sales, the industry is buzzing with Gen AI, which promises to shake up traditional sales models. While it's tempting to jump on the bandwagon, here's a nugget of wisdom: Generative AI is not just a flashy trend; it's a tool poised to redefine how sales and marketing interact with customers. Unlike its traditional counterpart, Gen AI crafts new, unique strategies and solutions, enhancing customer engagement and potentially offering a sustainable edge in an ever-competitive market. So, proceed, but with enlightened caution.

Understanding the specific use cases for Generative AI can illuminate not just its potential, but also its applicability to different business functions. Here they are:

1. Personalized Sales Pitches: Adapt your pitch in real-time, focusing on a prospect’s unique pain points and industry needs.

2. Dynamic Content Creation: Automated crafting of marketing collateral, from emails to social posts, that resonate with specific audience segments.

3. Customized Product Recommendations: Real-time, AI-driven suggestions for upselling or cross-selling, based on individual customer behavior and preferences.

4. Automated Follow-Up Communications: Timely, context-aware follow-up emails or messages post-interaction to keep the conversation going.

5. Virtual Sales Assistants: AI bots that handle the initial stages of customer engagement, freeing up human reps for more complex interactions.

6. Sales Conversation Summaries: Automated, comprehensive capture of sales dialogues, highlighting decisions, action items, and key discussion points.

7. Zero-Touch Case Resolution: Intelligent chatbot responses that can resolve queries without human intervention, based on historical patterns.

8. Intelligent Case Creation: If a chatbot can't resolve a query, it passes the case to a human agent, armed with summarized chat notes and suggested next steps.

9. Sales Forecasting and Prediction: Data-driven sales forecasts that factor in past performance, market conditions, and even external variables.

10. Automated Data Entry: Imagine CRM systems that automatically pull in key details from sales calls, emails, and meetings—ditch the manual data entry.

11. Sales Performance Reports: Auto-generated reports on key performance indicators, highlighting both wins and areas needing improvement.

12. Dynamic Pricing Strategies: Data-backed price adjustments that respond to market conditions and customer demand in real-time.

13. Lead Qualification and Scoring: Automatic vetting and scoring of leads, ensuring that sales teams zero in on the most promising prospects.

14. Customer Success Assistant: Summarized chat notes and recommended next steps to guide customer service agents in decision-making.

15. Automated Case Communications: Send follow-up emails or messages based on chat or agent notes, maintaining the dialogue and keeping it relevant.

Reference: (How to Infuse AI Into Your Current Sales and Marketing Processes)

🗞️ RESOURCES

IBM has boldly pledged to train 2 million people in AI skills within three years, targeting underrepresented communities. This strategic move aims to fill the widening AI skills gap, a challenge causing ripples across industries and magnifying social inequities. IBM's tactics are multi-pronged, from releasing new free courses on generative AI to global university partnerships. This venture aligns with a larger ambition to skill 30 million individuals by 2030. Indeed, it's an initiative that deserves applause, not just for its scale but for its inclusivity and future-forward focus.

Reference: (IBM Commits to Training 2 Million in AI to Address Skills Gap)

🗞️ WORK

Australia is caught in a high-stakes balancing act with generative AI, facing both a tantalizing AU $115 billion economic windfall and serious risks like data privacy and workforce disruption. As the talk shifts from novelty to necessity, IT professionals emerge as the linchpins, orchestrating the nation's approach to AI implementation. Surveys reveal businesses are eager yet cautious, employing generative AI sporadically. While the public sector inches towards responsible adoption, experts stress the need for a concerted, business-aligned strategy to fully capitalize on this revolutionary technology.

Reference: (Australia Is Adapting Fast to a Generative AI World)

🗞️ AI TOOLS

Mailivery: Land in the Inbox. Not the Spam Folder. Maximize Email Deliverability

Gamma: A new medium for presenting ideas. Powered by AI. Just start writing. Beautiful, engaging content with none of the formatting and design work.

Supermeme: Turn text into memes using AI Meme Generator

SheetGPT: The Power of AI in Google Sheets. SheetGPT is the easiest way to integrate OpenAI's text and image generation in your Google Sheets™

OneShot: OneShot uses AI & machine learning to pinpoint ideal leads and generate highly personalized, ChatGPT-powered messaging.

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

 👀 Chief Data Officers face not just a data management dilemma, but the more nuanced task of fostering a data ecosystem that maximizes generative AI’s potential. The path forward involves seven cardinal steps: explicit value targeting, tailoring data architectures, meticulous quality checks, pre-emptive data security, nurturing engineering talent, utilizing generative AI for data curation, and a continuous loop of performance metrics and adjustments.

Source/Credit: McKinsey & Company (The data dividend: Fueling generative AI)

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].}