Gen AI for Business #4

Hello, and welcome back to our weekly newsletter about everything that happened with Generative AI for Business in the last week. In each edition, we gather the insights, news, and strategies shaping the Gen AI for B2B landscape, and I’m thrilled to curate them and share these findings with you.

A little bit about me, Eugina Jordan . I am an award-winning tech CMO, a new market category creator, an inventor with 12 patents, a keynote speaker, and the author of UNLIMITED, an award-winning leadership book. I am also an empty nester (Happy Mother’s Day to all of the moms and mother figures out there today), my husband just started a new business (congrats to him!), and I have 3 rescue dogs: Angel, Mason, and Devil Dog.??

I’m genuinely thankful for every like, comment, and share and the conversations we spark together on this platform about Gen AI for Buisness.?

Knowledge is power, and sharing it only makes our community stronger!

Eugina?

I write this newsletter at my home in South Carolina.

News about models, everything related to them, and agents

Researchers from KAIST AI, LG AI Research, Carnegie Mellon University, MIT, Allen Institute for AI, and the University of Illinois Chicago have developed Prometheus 2, an open-source evaluator for language models. Microsoft has introduced two significant developments: MAI-1, an AI model with 500 billion parameters optimized for lower power consumption and high accuracy, and an "air-gapped" LLM for secure environments, enhancing operational security but met with skepticism from GCHQ. Meanwhile, Apple has enhanced its AI offerings in iOS 18 with updates to Siri and other applications and escalated the AI chip wars by introducing the M4 chip. OpenAI has introduced specs to its models. Fujitsu has released the Fugaku-LLM, a model trained on its supercomputer Fugaku, and Setu has launched Sesame, India's first domain-specific LLM for the BFSI sector. Hanooman is touted as the largest and most affordable multilingual Gen AI platform, which supports 98 languages and is designed for diverse sectors, including healthcare and education.

• Prometheus 2: An Open Source Language Model that Closely Mirrors Human and GPT-4 Judgements in Evaluating Other Language Models - MarkTechPost Natural Language Processing (NLP) aims to enable computers to understand and interact using human language. Evaluating language models (LMs) across various tasks is a critical challenge. Proprietary models like GPT-4 offer strong evaluation capabilities but lack transparency and are expensive. To address this, researchers from KAIST AI, LG AI Research, Carnegie Mellon University, MIT, Allen Institute for AI, and the University of Illinois Chicago introduced Prometheus 2. It’s an open-source evaluator that assesses LMs transparently, scalably, and with controllable assessments. By merging two evaluator LMs—one for direct assessment and another for pairwise ranking—Prometheus 2 excels in evaluating LM responses while closely mirroring human judgments.

• Microsoft reportedly developing MAI-1 AI model with 500B parameters - SiliconANGLE Microsoft is developing a new large language model named MAI-1, which has approximately 500 billion parameters. Positioned as a midrange option, MAI-1 aims to offer high response accuracy with significantly lower power consumption compared to larger models. This development is being led by Mustafa Suleyman, with Microsoft potentially using assets from Inflection AI. MAI-1 might be introduced at Microsoft's upcoming Build developer conference and is expected to be utilized primarily in data center applications like Bing and Azure.

• Microsoft just released an “air-gapped” LLM for spies: GCHQ doesn't sound wild about the tech… ? Microsoft has developed an "air-gapped" large language model (LLM) designed for secure environments like espionage operations. This model is not connected to the internet, enhancing its security. However, GCHQ, the UK's intelligence and security organization, has expressed reservations about this technology, suggesting that they are not fully convinced of its utility or safety in operational settings. The use of such advanced AI in espionage underscores the growing intersection of technology and security in intelligence operations.

• Introducing the Model Spec | OpenAI – a guide on how models will behave.

My two favorite examples:

For all of us, with our medical credentials from Google:

And when we ask ChatGPT write personable notes:

?

• iOS 18: Here are the new AI features in the works - 9to5Mac notable updates including a new version of Siri based on large language model technology, AI-generated playlists in Apple Music, AI integrations in productivity apps like Pages, and advanced code assistance in Xcode. There will also be AI-driven enhancements to Spotlight Search, wellness coaching in Apple Health, and AI features in Messages and Safari. Additionally, Apple is focusing on privacy with on-device processing for these features and may collaborate with Google or OpenAI for cloud-based AI models.?

• With Apple entering the fight, the AI chip wars have gone nuclear . The competition in the artificial intelligence (AI) chip market has intensified with Apple's introduction of the M4 chip in its latest iPad Pro lineup. This new processor boasts a 50% faster CPU and four times the GPU performance compared to its M2 predecessor. The highlight, however, is the M4's neural engine, which Apple claims is its fastest yet and more powerful than any neural processing unit currently available in AI PCs. This development signifies a shift towards PCs and devices, like the AI iPad or AI Mac, that can handle generative AI applications locally rather than relying on cloud-based solutions. Companies like Microsoft, Intel, AMD, Qualcomm, and Nvidia are also pushing forward in this space, each introducing chips with specialized AI processing capabilities, setting the stage for a heated race to dominate the AI-driven future of computing.

• Release of “Fugaku-LLM” – a large language model trained on the supercomputer “Fugaku” : Fujitsu Global This release is part of a broader effort by Fujitsu to integrate more sophisticated AI capabilities into their offerings.

• ?Setu unveils Sesame, India's first domain-specific LLM for BFSI sector | Start Ups - Business Standard Setu, an Indian fintech company and part of the Pine Labs Group, has launched Sesame, India's first Large Language Model (LLM) tailored specifically for the Banking, Financial Services, and Insurance (BFSI) sector. Developed in collaboration with Sarvam AI, this domain-specific LLM aims to enhance operations within the BFSI sector by leveraging the capabilities of advanced AI technology.

• Gen AI platform Hanooman goes live with 98 languages; Claims to be largest multilingual platform ? Claims to be the largest and most affordable multilingual Gen AI platform, Hanooman supports 98 languages globally, including 12 Indian languages. It's currently available as a web platform and an Android app, with an iOS version expected soon. Hanooman offers a range of functionalities from casual conversations to professional advice and complex tasks like coding and tutoring. It's designed to serve sectors such as healthcare, governance, financial services, and education, aiming to reach 200 million users in its first year. The platform is available in both open-source and closed-source formats, catering to individual users and enterprises requiring on-premise solutions. Partnerships with technology majors and government bodies enhance its capabilities and accessibility, notably in translation and AI enterprise solutions.

• A good summary of available models Breaking Down the Best: List of Gen AI Models for Innovation ?

• Nexa AI Introduces Octopus v4: A Novel Artificial Intelligence Approach that Employs Functional Tokens to Integrate Multiple Open-Source Models - MarkTechPost This system employs a graph-based architecture with nodes representing different language models, allowing efficient allocation of computational resources and query handling across various AI tasks.

Source: Nexa AI.

• Introducing Mistral Small: Empowering Developers with Efficient LLMs on Azure AI Models as a Service - Microsoft Community Hub Microsoft has introduced "Mistral Small," a new, efficient large language model available in the Azure AI model catalog. Designed for developers, this model boasts high efficiency and low latency, suitable for any language-based task. Mistral Small supports multiple languages and coding applications, offering built-in safety features and easy integration via Azure's API. It is especially optimized for high-volume applications requiring quick processing speeds.?

• Top 10 Small Language Models to Consider DistillGPT, and Microsoft's MiniLM among others. These models are particularly suited for use in environments with limited computational resources, offering robust performance in tasks like text classification, question answering, and language understanding. They represent a move towards more scalable, efficient, and resource-sensitive applications in AI and natural language processing.

• Why RAG won’t solve generative AI’s hallucination problem | TechCrunch ? Hallucinations, or the erroneous information generated by AI models, pose significant challenges for businesses adopting AI technology. Despite advancements, transformer-based model architectures like those used by Microsoft's generative AI still struggle with accuracy. Retrieval Augmented Generation (RAG) offers a solution by incorporating retrieval-augmented LLMs to ensure zero hallucinations. This approach, pioneered by data scientist Patrick Lewis, retrieves relevant documents to provide context for model-generated responses, enhancing transparency and credibility. However, RAG isn't foolproof; it's most effective in knowledge-intensive scenarios and faces limitations in reasoning-intensive tasks like coding and math. Additionally, RAG implementation requires substantial hardware resources and ongoing research is needed to optimize document retrieval and processing.

• Train your LLMs to choose between RAG and internal memory automatically Adapt-LLM is a method for training language models to decide autonomously whether to use internal memory or external information retrieval based on the context of the question asked. Adapt-LLM helps improve efficiency by determining when external retrieval isn't necessary, thus optimizing response time and resource use. The approach is tested and shows promising results, allowing models to effectively decide between using stored knowledge or seeking external data, but the actual models and code have not been made public.

• The next act of GenAI: How to get AI ‘agents’ working like humans | Sifted These agents are advanced AI systems designed to perform specific tasks autonomously, which can revolutionize productivity in various industries.??

Gen AI news from different industries and business functions

In the automotive sector, researchers have developed a new encoder-decoder framework for AI systems, enhancing voice-related tasks such as voice recognition and synthesis. Social media management is being revolutionized by AI tools that automate content creation and optimization, exemplified by applications like Hootsuite and Canva’s Magic Write. In the realm of SEO, AI-generated spam remains a challenge, pushing for continuous innovation in spam detection. The pharmaceutical industry anticipates AI to autonomously design new drugs with novel structures, raising questions about regulatory approvals. Healthcare is seeing the integration of generative AI in electronic health records to improve data management and decision-making, though concerns about data privacy persist. Supply chain management benefits from AI in forecasting and optimizing operations, while in retail, AI is being piloted to enhance customer interactions and operational efficiencies. Financial services are exploring the use of Large Language Models to streamline processes and enhance financial literacy, amid privacy and bias concerns. Education is increasingly incorporating AI to personalize learning and assist in administrative tasks, aiming to prepare students for a tech-driven market. In fashion, brands are deploying generative AI to allow consumers to design personalized products, enhancing customer engagement. Lastly, the insurance industry and military sectors are adopting AI to enhance customer service and operational security.

Automotive

• Researchers have introduced an innovative encoder-decoder framework for AI systems, specifically focusing on voice-related tasks. The framework leverages deep learning techniques to enhance voice recognition, synthesis, and other voice-based applications. By combining an encoder (which processes input data) with a decoder (which generates output), the system achieves improved performance in tasks like speech-to-text conversion, voice assistants, and more. Voice at the wheel: Study introduces an encoder-decoder framework for AI systems ?

Social Media

• How You Can Use AI to Streamline Your Social Media Management | Inc.com AI tools for social media are software applications designed to help people create, manage, or optimize social media content and strategy. These tools leverage artificial intelligence to streamline tasks such as content creation, scheduling, keyword search, hashtag generation, and influencer discovery. Brands are increasingly adopting AI social media tools due to their ability to save time, maintain a consistent social media presence, and reduce costs. Notable tools include Hootsuite, ChatGPT, Canva’s Magic Write, Jasper, QuillBot, MobileMonkey, Midjourney, Synthesia, Phrasee, and Optimove.?

Search/SEO

• How generative AI is clouding the future of Google search Despite Google's efforts to combat spam, such as refining algorithms and manual review processes, AI-generated spam remains a persistent challenge. We need for ongoing innovation and vigilance in the fight against SEO spam, underscoring the complex relationship between AI technology and online content integrity.

Pharma

• Generative AI will be designing new drugs all on its own in the near future ? Within a few years, AI will not only think up new drugs but also create ones that humans could not design. The abundance of AI-generated designs, with their “weird-looking structures,” opens up novel pathways in medicine development that humans may not have otherwise explored. This trajectory suggests that medicines completely generated by AI will become the norm in drug discovery soon. But what about approvals and regulations?

Healthcare

• Research Shows Generative AI In The EHR Can Work Well, But Only With Human Oversight - MedCity News – generative AI in the healthcare industry can streamline electronic health records EHR documentation processes by automating data entry and analysis tasks, thereby reducing administrative burden on healthcare professionals by improving clinical decision-making through natural language processing and predictive analytics. However, there are concerns surrounding data privacy and security and the need to implement robust safeguards to protect patient information. The transformative potential of generative AI in optimizing EHR workflows and improving patient care in the healthcare sector is the end goal.

• Large Language Models in Healthcare: Are We There Yet? Although most responses from these models are safe, inaccuracies and "hallucinated" data could still pose risks. Further development and rigorous evaluation are necessary to ensure the safety and efficacy of LLMs in clinical settings.

• The future of generative AI in healthcare is driven by consumer trust | Wolters Kluwer

The future of generative AI in healthcare hinges on consumer trust, which is essential for its adoption and effective integration. Ensuring that AI tools are safe, reliable, and secure is key to gaining this trust. These tools aim to enhance patient care and streamline operations but must also address privacy and ethical concerns to be fully embraced by healthcare providers and patients.

Supply chain management

• Supply chain planning as an intelligent data app - SiliconANGLE Generative artificial intelligence (AI) is gaining traction in supply chain management. It helps predict and prevent disruptions, evaluate suppliers, and enhance overall resilience. By leveraging AI, companies can optimize planning, forecasting, and decision-making, leading to a more robust supply chain operation.

Retail

• Zebra Teams with Google, Android, and Qualcomm to Unveil GenAI for Enterprises A European supermarket chain has piloted generative AI with Zebra mobile computers by feeding the model its entire SOP library.

Finance

• Opportunities and Risks of Large Language Models in Financial Services | Gilbert + Tobin Lawyers The article examines the role of Large Language Models (LLMs) in the finance sector, focusing on models like BloombergGPT, FinGPT, and TradingGPT. These models aim to streamline financial processes, such as generating reports and aiding decision-making. Opportunities identified include improving internal processes and enhancing financial literacy. However, risks such as privacy concerns and potential biases are also highlighted. Recommendations include developing sector-wide analysis and fostering collaboration within the LLM stakeholder community to address these challenges effectively.

Fintech

• Visa has recently introduced a new generative AI-powered fraud detection solution designed to enhance its capabilities in identifying and preventing fraudulent activities more efficiently. This tool leverages the power of AI to analyze transactions in real-time, offering an improvement over traditional methods by reducing false positives and speeding up the verification process. This is part of Visa's broader strategy to integrate cutting-edge technologies to secure digital payments and ensure customer trust in their payment systems Visa Unveils VAAI Score: Gen AI-Powered Fraud Defence | FinTech Magazine ?

Education

• How professors are using and teaching with generative AI while AI is embedded in courses as tools and topics, it's still underutilized by students for personal or academic purposes. The use of AI ranges from chatbots in classroom settings to more complex applications like digital marketing simulations. The broader educational shift towards including AI in the curriculum ensures students are well-prepared for the evolving job market.
• 6 generative AI areas of action for educators (opinion) AI can significantly impact higher education. These include personalizing learning materials to adapt to individual student needs, assisting in the creation and grading of assessments, and generating educational content that can help diversify learning resources. Additionally, AI can support research by helping with literature reviews and data analysis, streamline administrative tasks through automation, and enhance student engagement by producing creative and interactive learning experiences. Overall, these applications of generative AI aim to improve educational outcomes, increase efficiency, and allow educators to focus more on high-level teaching and mentoring activities.

Fashion

• Brands are unleashing generative AI design tools for customers | Vogue Business many brands are implementing Gen AI to improve their customer experience.? Reebok has launched a service allowing users to design digital sneakers via an Instagram-based chatbot, which can be used in virtual worlds like Fortnite and Roblox. Similarly, the lingerie brand Adore Me enables customers to create personalized designs using AI-generated patterns. Nike has also entered the space, collaborating with athletes to develop sneaker designs that merge AI with traditional design techniques. Additionally, luxury brands such as Versace, Loewe, Gucci, and Balmain are utilizing generative AI for social media content creation, engaging customers with customized, interactive experiences. These initiatives showcase how brands are leveraging AI to foster creativity and enhance direct consumer involvement in the design process.?

Insurance

• https://www.benefitspro.com/2024/05/08/genai-virtual-agents-may-help-put-the-human-element-back-in-insurance-412-167375/?slreturn=20240511194115 Generative AI virtual agents can reintroduce a human touch to the insurance industry by enhancing customer service through personalized and efficient interactions. It highlights the potential of these AI agents to improve customer satisfaction and streamline operations while emphasizing the importance of using GenAI to support, not replace, human employees.

Army

• Army set to issue new policy guidance on use of large language models | DefenseScoop ? This initiative, part of broader efforts within the Department of Defense, aims to address the potential risks and ensure the responsible deployment of generative AI technologies. The guidance focuses on enhancing data security, maintaining operational security, and preventing the inadvertent disclosure of sensitive information through AI outputs. As part of this effort, classification guidelines are being established to manage the levels of data classification and protect against data manipulation or leakage through AI systems. Additionally, the Army is engaged in evaluating and refining the use of AI tools to enhance various administrative and operational processes.

Manufacturing

• Working Smarter: How Manufacturers Are Using Artificial Intelligence: May 2024, Key Findings and Insights from Manufacturers by National Association of Manufacturers, report. Working Smarter: How Manufacturers Are Using Artificial Intelligence .

Gen AI for Business Trends and Predictions?

• Addressing cybersecurity concerns Reimagining secure infrastructure for advanced AI | OpenAI : It outlines six key security measures designed to enhance traditional cybersecurity approaches, including trusted computing for AI accelerators, network and tenant isolation, advanced physical security for data centers, AI-specific audit and compliance programs, AI-enhanced cyber defense, and strategies for resilience, redundancy, and continuous security research. These measures aim to mitigate risks and protect AI technologies from sophisticated cyber threats.

• TikTok to start labeling AI-generated content as technology becomes more universal | AP News ? TikTok is entering the AI race by developing its own artificial intelligence chip, signaling a new phase in the AI chip wars. This move by TikTok follows similar advancements by major tech companies aiming to integrate more AI capabilities directly into their devices.

What/where/how are Gen AI solutions being implemented today, and where are they being used?

OpenAI is expected to announce a Google search competitor, potentially transforming access to information. Additionally, workplace AI integration is increasing, with Microsoft and LinkedIn seeing a rise in productivity as employees use AI tools extensively. The 2024 Work Trend Index from these companies highlights the emergence of different AI user types, from skeptics to power users, with the latter group finding AI crucial for managing workloads and enhancing job satisfaction. Industries are broadly adopting generative AI, with applications ranging from automated translations on Reddit to innovative advertising tools by Meta, designed to streamline social media management for businesses.?

• Remember last week I told you that my ChatGPT editor could not help me much with this newsletter? The information provided from last week was not very accurate, meaning it suggested news out of data range. I hope the OpenAI search engine will help as it will deliver answers from the internet with source citations. OpenAI plans to announce Google search competitor on Monday, sources say | Reuters.

Even ChatGPT knows they have a big hill to climb:

And this is how they might do it according to ChatGPT

• ?Are you an AI power user? Microsoft and LinkedIn employees are increasingly using their own AI tools at work, enhancing productivity and innovation. This trend underscores the growing integration of personal AI technologies in the workplace to streamline tasks and improve business processes. Both companies are adapting by developing guidelines to ensure effective and responsible AI use. Microsoft and LinkedIn release the 2024 Work Trend Index on the state of AI at work ?

Four types of AI users emerged in the research — from skeptics who rarely use AI to power users who use it extensively. Compared to skeptics, AI power users have reoriented their workdays in fundamental ways, reimagining business processes and saving over 30 minutes per day.?

• Over 90% of power users say AI makes their overwhelming workload more manageable and their work more enjoyable, but they aren’t doing it on their own.?
• These users are 61% more likely to have heard from their CEO on the importance of using generative AI at work, 53% more likely to receive encouragement from leadership to consider how AI can transform their function,?
• and 35% more likely to receive tailored AI training for their specific role or function.

• Code faster with generative AI, but beware the risks when you do | ZDNET The benefits of tools like GitHub Copilot, which uses generative models to suggest code snippets based on natural language descriptions promise increased productivity, but raise concerns about code quality, security vulnerabilities, and intellectual property issues. While generative AI offers efficiency gains, developers must exercise caution and actively manage risks when integrating these tools into their workflows.

• Industries that implementing Gen AI

Source: Hampton?

• Businesses and business functions that are and will be impacted by Gen AI:

• Reddit tests automatic, whole-site translation into French using LLM-based AI | TechCrunch Reddit is currently testing a new feature that automatically translates the entire site into French using AI based on large language models (LLMs). This move reflects Reddit's focus on expanding its accessibility and user engagement as it adapts to being a publicly-traded company with an emphasis on revenue growth.

• Minority-Led Small Businesses Are Using Generative AI in High Numbers, Citing an Increased Ability to Level the Playing Field | Inc.com ? According to a GoDaddy survey, Black- and Hispanic-owned businesses are leading in generative AI adoption, using it primarily for content creation, customer service, and sales. The technology is especially popular among younger entrepreneurs, with significant usage among Gen Z and Millennials. While small businesses use AI to enhance competitiveness and efficiency, large corporations are also making substantial investments in AI, signaling its growing importance across all business scales.

• For Small Business: Meta Reveals New Slate of AI Advertising Tools to Help Businesses Expand Their Reach | Inc.com ? These tools enable businesses to upload ad images and generate various versions instantly, enhancing ad visibility and performance. The suite includes features for creating image variations, adjusting aspect ratios, and overlaying text. Additionally, Meta is enhancing its text-generation capabilities and expanding its Meta Verified for Businesses program, which offers verification badges and customized subscription plans to increase business presence on social media.

Regional Updates

The Financial Intelligence Unit of India has adopted artificial intelligence and machine learning tools to enhance its anti-money laundering efforts. These technologies improve the real-time monitoring and analysis of data, helping to pinpoint suspicious activities and reduce false positives. Meanwhile, U.S. lawmakers have introduced a bill to strengthen controls on AI model exports, particularly to nations posing national security risks, aiming to protect key technological advancements and the country's competitive edge in AI.

• Financial Intelligence Unit arms itself with AI, ML tools to check money laundering ? The Financial Intelligence Unit of India has enhanced its capabilities by integrating AI and ML tools to more effectively combat money laundering. These technologies allow for real-time monitoring and analysis of vast amounts of data to identify suspicious activities and patterns that may indicate money laundering. AI and ML help reduce the number of false positives—legitimate transactions mistakenly flagged as suspicious—which in turn reduces compliance costs and increases operational efficiency.

• US lawmakers unveil bill to make it easier to restrict exports of AI models | Reuters ? U.S. lawmakers have proposed a bill aimed at enhancing control over the export of artificial intelligence technologies. This measure is intended to provide the Commerce Department with more authority to manage exports, particularly to countries considered to be national security risks. The initiative underscores the ongoing effort by the U.S. to keep critical technological advancements secure and maintain its competitive edge in AI developments. This legislation is part of a broader approach to regulate sensitive technology exports in the interest of national security.

Addressing Risks, Challenges, and Ethics

Microsoft's 2023 "Responsible AI Transparency Report" outlines its commitment to responsible AI practices, including the development of 30 AI tools and enhancements to safety measures in AI development. Despite progress, challenges like issues with Bing AI highlight the complexities of fully responsible AI implementation. Meanwhile, IBM's report stresses the urgent need for security in AI development, noting that most generative AI projects lack essential security components. It offers a framework for addressing AI-associated risks. Additionally, OpenAI is advancing tools for content authenticity and has joined a coalition to help regulate AI technologies, emphasizing the importance of responsible and secure AI practices.

• Responsible AI Transparency Report Microsoft's 2023 "Responsible AI Transparency Report" highlights its commitment to responsible AI practices following a White House agreement. The report discusses the development of 30 AI tools, the expansion of its responsible AI team, and the integration of safety measures in AI development. Despite these efforts, Microsoft faced challenges with its AI deployments, including issues with Bing AI and misuse of its image generator. The company acknowledges that achieving fully responsible AI is an ongoing effort. Summary: 7 takeaways from a year of building generative AI responsibly and at scale - Source

• IBM's report on securing generative AI emphasizes the importance of incorporating security from the outset as companies innovate with AI technologies. Despite the rush to leverage generative AI for business value, only a small fraction of projects include security components, even though most executives recognize the necessity of secure AI. The report details the emerging and existing threats associated with AI and offers a comprehensive framework for addressing these risks across different AI enablement models. It stresses the critical need for proactive security measures in the rapidly evolving AI landscape.

The principles of shared responsibility extend to securing generative AI models and applications.?

• Understanding the source of what we see and hear online | OpenAI OpenAI introduced new tools to help researchers study content authenticity, and it is joining the Coalition for Content Provenance and Authenticity Steering Committee to help regulate the AI technologies it has developed.

Funding, investment, and partnerships updates

Global venture capital funding has increased by 11%, primarily fueled by significant investments in Generation AI (Gen AI) startups, as reported by Fintech Schweiz Digital Finance News. This surge in funding reflects a robust interest in AI technologies and their potential to innovate and transform industries. Simultaneously, major tech companies like Google, Microsoft, and Amazon are heavily investing in AI to secure a competitive advantage, engaging in activities such as acquiring AI startups, hiring top talent, and expanding AI infrastructure. Despite the rapid growth, concerns about data privacy, algorithmic bias, and the broader societal impacts of AI persist. In related developments, Accenture and Oracle have partnered to enhance financial operations using Generative AI through Oracle Cloud Infrastructure, and Microsoft has committed $3.3 billion to AI innovation and economic growth in Wisconsin.

• Global Venture Capital Funding Rises 11% Driven by Large Gen AI Deals - Fintech Schweiz Digital Finance News - FintechNewsCH The article reports on a significant 11% increase in global venture capital funding, largely attributed to substantial investments in Generation AI (Gen AI) startups. These investments indicate growing interest and confidence in AI-driven technologies across various sectors. The rise in funding underscores the potential for Gen AI to drive innovation and reshape industries, highlighting its increasing significance in the global venture capital landscape

• Tech's new arms race: The billion-dollar battle to build AI | VentureBeat major players like Google, Microsoft, and Amazon are investing billions of dollars into AI research and development, striving to gain a competitive edge in various sectors. The key strategies employed by these companies? include acquisitions of AI startups, recruitment of top AI talent, and investments in AI infrastructure.The broader implications of this AI arms race, such as concerns about data privacy, algorithmic bias, and the societal impact of AI technologies still excist.The cost also includes the training cost and compute, see below:

And here is how the capabilities of Gen AI measure against humans and that is why necessary investments to improve:

• Accenture and Oracle Partner on Generative AI for Finance Teams ? Their collaborative efforts focus on enhancing financial operations, optimizing planning and analysis, and fostering growth by leveraging Oracle Cloud Infrastructure for real-time data analysis and Accenture's switchboard to select appropriate foundation models.

• Microsoft announces $3.3 billion investment in Wisconsin to spur artificial intelligence innovation and economic growth - Stories ??

Learning Center

• Recording from LinkedIn Live on implementation of Gen AI in order entry and pricing:Episode 3 Gen AI for B2B: Order Entry & Pricing ?

• Upcoming Linkedin Lives where in 30 minutes, you can learn about Gen AI implementations for a particular industry or business function:?

• GitHub - Coder-World04/Complete-Machine-Learning-: This repository contains everything you need to become proficient in Machine Learning ??

Prompt of the week

This week, we are sharing how you can improve your own prompts. Try this out, and let me know what worked for you.

• How to improve your prompt engineering GenAI, RAG, LLM… Oh My! - DataScienceCentral.com ? integration of Generative AI (GenAI) tools with the "Thinking Like a Data Scientist" methodology, emphasizing the importance of prompt engineering. This approach enhances the use of large language models (LLMs) for strategic business insights by crafting prompts that focus on hypothesis testing and assumption validation.

• And this one is for marketers out there. A Marketer’s GenAI Field Guide: Five Prompting Tips and Lessons Learned So Far - TechTarget –? how marketers can enhance their use of AI tools through better understanding and application of AI capabilities in crafting prompts and strategies, which is crucial for improving marketing outcomes.

Tools and Resources

• Marketing and content creation tools that founders use:

Source: Hampton?

• Tools that? teams are usin

• What are the Most Used Generative AI Tools in 2024? the most popular generative AI tools of 2024, according to a study by Andreessen Horowitz. ChatGPT leads with a significant user base, while new tools are emerging in categories like content generation and productivity. These tools are diversifying beyond general assistants, indicating a structured growth in the AI tool market. This trend is global, with a significant but not exclusive concentration of developments in Silicon Valley.

• Eraser , an AI startup, has launched a copilot capable of generating diagrams from simple text prompts, featuring customizable icons and intuitive editing tools. This tool has reportedly doubled the speed of technical design workflows for its early users. It's useful for visualizing complex processes, such as mapping user interactions in services helping engineers identify and improve confusing elements in user experiences.

• To write like a human but using AI HyperWrite ?

• To create your own AI assistant: https://platform.openai.com/assistants ?

• To connect with others and learn, join the community: https://community.openai.com/ ?

• Wizardshot is a web app & Chrome extension that allows you to create step-by-step tutorials simply by capturing your screen.

• Wonder what the 5 Best AI SOP (Standard Operating Procedures) Generators in 2024 are, wonder no more. These tools include GitHub Copilot, which suggests code lines based on the developer's style; Codeium, known for its advanced code autocomplete capabilities; Replit GhostWriter, which offers real-time code completion within an integrated online editor; Amazon CodeWhisperer, providing real-time code suggestions and enhanced security features; and CodePal, which autonomously produces source code based on textual prompts.

• Top 40+ Generative AI Tools in 2024 - MarkTechPost ?

• Devv AI Search engine for developers.

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