Gen AI in News March 2024

Gen AI Unicorns:

In March 2024, the Generative AI landscape significantly grew. Couple of companies reached the unicorn status

1. Anyscale: AnySale raised a Series C round at a USD $1.01 Billion valuation in 2022, and its platform is used by OpenAI and others for AI development, training and fine-tuning. Anyscale also teamed with Nvidia to Supercharge LLM performance and efficiency in Sept 2023. It also launched new service Anyscale Endpoints, 10X more cost-effective for most popular open-source LLMs. This is now reaching a stage of unicorn. Refer to MarketLine Advantage for Anyscale deals information.
2. Jasper AI Writing Tool: Jasper, an AI writing tool that assists businesses in creating content, which secured valuation of USD $ 1.5 Billion following a Series A funding round of USD $ 141 Million.
3. Stability AI: Known for being behind Stable Diffusion, and Hugging Face, a community and data science platform for building and deploying ML models has reached / surpassed the unicorn valuation, with Stability AI valued at USD $ 1.0 billion (and Hugging Face at USD $2.0 Billion).

Noteworthy Generative AI Conferences or Symphosiums:

March 2024:

1. NVIDIA’s GTC 2024: March 18–21 2024 in San Jose, CA, a premium event for Developers, business leaders and AI researchers. Covered a wide range of topics including robotics, automative workflows with Large Language Models, IP challenges and the global regulations of AI. Panel featuring the authors of the seminal paper “Attention is all you need” was moderated by Jensen Huang, NVDIA CEO.
2. Chatbot Summit 2024: Berlin from March 19–21, 2024. A leading conference for Generative and Conversational AI featuring workshops, success stories with conversational AI, and opportunities for networking with leaders in the field.
3. C3 Transform 2024: Hosted by C3 AI from March 5–7, 2024 in Boca Raton, Florida, conference focuses on how Generative AI is delivering productive and efficiency benefits across industries. Presentations are available in the link.
4. AI in Drug discovery: March 11–12 2024, in London UK, the conference explored the latest AI advancements across the Pharma sector.

April 2024:

In April 2024, there are several notable events focusing on generative AI and large language models. Few of them include

1. AI/Machine Learning for Early Drug Discovery: A two-part conference discussing AI/ML’s role in drug development, focusing on drug design, hit identification, and lead optimization. (San Diego, CA, April 1–4)

2. 2024 IAC: A leading gathering for information architecture professionals, offering insights into user experience design and content strategy. (Seattle, WA, April 9–13)

3. MPLS SD & AI: Highlighting edge/cloud applications and Open RAN implementations, with sessions on IPv6/only networks and AI/ML automation. (France, April 9–11)

4. CMLDS 2024: Covers innovations in computing, machine learning, and data science, aiming to share research outcomes and foster interdisciplinary dialogue. (Singapore, April 12–14)

5. AI Accelerator Summit: Showcases scalable solutions and industry-leading applications of AI, focusing on ethical AI projects and customer-centricity. (San Jose, CA, April 17–18)

6. AI & Metaverse Innovate Summit 2024: Pioneering the future of digital business (Virtual, 17–18 April 2024)

7. AIAPP 2024: Brings together researchers and practitioners to discuss new advances in AI, with a focus on Artificial Intelligence applications. (Australia, April 20–21)

8. 3rd Tech Summit on Artificial Intelligence & Robotics: Emphasizes AI and robotics’ role in current and future technologies. (Narita, Japan, April 22–23)

9. AIRC 2024: A forum for scholars in AI, robotics, and control to share research and foster collaborations. (Egypt, April 22–24)

Gen AI Product Launches:

1. Thomas Reuters: Unveiled Generative AI solutions at the Synergy 2024 Legal Conference in Sydney, targeting the legal profession. The conference was aimed at exploring future legal innovation.
2. NVDIA launched generative AI Microservices for developers, enabling the creation and deployment of Generative AI Copilots across its CUDA GPU installed base. This includes a new catalog of GPU-accelerated microservices and cloud endpoints for pre-trained AI models optimized for CUDA-enabled GPUs across various platforms.
3. The University of California, Irvine: Introduced ZotGPT chat, a customized generative AI solution designed to allow UC Irvine affiliates to explore AI in a safe, tailor-made environment. This tool is aimed at transforming work and interactions within the community.
4. Google’s investment in the Generative AI Startup Anthropic.
5. AWS collaboration with DeepBrain AI and Amazon’s partnership with Anthropic to develop reliable generative AI models.

Industry or Sub-Industry using Generative AI:

1. Film and Entertainment: Ever wanted to direct a movies without people involved and get them released? It is now possible with companies like Runway are pioneering in creating generative video models, producing video content with quality comparable to Pixar’s work. This technology is being used for lip-syncing actors’ performances in multiple language and enhancing special effects, with significant interest from major studios like Paramount and Disney. Additionally, the deployment of deepfake technology for marketing and training signifies its expanding role beyond traditional film production.
2. Fashion: Generative AI is enabling collaboration between brands and personalize / customize the products suggestions such as eyeglasses to individual personal preferences. Gen AI enables designers to experiment with an endless variety of styles by inputting sketches and desired details into AI powered platforms significantly accelerating the design process. This opens new avenues for creating limited-edition product.
3. Finance and Trading: Financial services are leveraging generative AI for risk assessment, fraud detection, algorithmic trading, and enhancing customer service through chatbots. IT also helps to detect unusual patterns or ability to establish network of connections that optimizes the trading strategies.
4. Marketing and Advertising: Transformative tasks that previously took hours into minutes without sacrificing creativity. AI-generated content tools are revolutionising content creation, targeted advertising and gaining consumer insights, enabling marketers to engage their audience more effectively.
5. Manufacturing (Industry 4.0): Undergoing a revolution with Industry 4.0, where Generative AI helps drive efficiency, productivity and innovation. Applications range from predictive maintenance, minimizes unnecessary downtime and costs, to optimise product design and supply chain management.
6. Software Development: Impact of Generative AI on programming and software development is notable, with AI improving the productivity be it using Copilot or AI Assisted programming enables substantial productivity gains.

Generative AI and Cloud Providers:

The world of cloud computing and generative AI is buzzing with new developments this month. Key partnerships and funding rounds are setting the stage for innovative expansions and offerings. Here’s a quick roundup of some significant moves in the industry.

1. AWS Generative AI: AWS positions itself as a leader for businesses looking to innovate with generative AI. It offers Claude 3 Haiku from Anthropic as part of Amazon Bedrock, which facilitates the building and scaling of generative AI applications. AWS is celebrated for its enterprise-grade security, access to leading foundation models, and an array of generative AI-powered applications like Amazon Q and Amazon CodeWhisperer. Amazon SageMaker JumpStart and Amazon Bedrock provide the infrastructure and tools necessary for utilizing leading foundation models, customizing them with specific data, and ensuring privacy and responsible AI practices from the outset.

AWS, Accenture, and Anthropic Partnership:

AWS has teamed up with Accenture and Anthropic to help organizations, especially in highly-regulated industries like healthcare and banking, adopt and scale customized generative AI technology responsibly. This collaboration is set to improve customer service, speed up innovation, and enhance workforce productivity while ensuring data privacy and security. Through Amazon Bedrock, organizations can access Anthropic’s advanced AI models and benefit from Accenture’s services to customize and fine-tune these models for specific needs. This initiative underscores a shared commitment to pushing the boundaries of AI while adhering to the highest standards of security and ethical AI use .

Claude 3 Sonnet Model on Amazon Bedrock:

Anthropic’s Claude 3 Sonnet foundation model is now available in Amazon Bedrock, bringing enhanced performance, speed, and steerability to AWS customers. Claude 3 Sonnet is designed to be twice as fast as its predecessors for the majority of workloads, with improved capabilities for tasks requiring rapid, intelligent responses. Its increased steerability and new image-to-text vision capabilities make it an ideal choice for a wide range of applications, including content generation and knowledge retrieval .

2. Azure and Generative AI: Azure shines with its close partnership with OpenAI, providing access to powerful models like text-davinci-003 and gpt-35-turbo. Azure ML offers an integrated environment for training, tuning, and deploying generative AI models efficiently. The platform emphasizes Microsoft’s comprehensive suite of tools for collaboration and productivity, high standards of security and compliance, and features like the Semantic Kernel for C# and Python developers. Azure’s capabilities in managing data with Azure Cosmos DB and Redis Enterprise, alongside its interoperability across different cloud environments, make it a strong candidate for generative AI projects .

Microsoft and NVIDIA Deepen Collaboration

Integration Galore: Microsoft Azure is set to adopt NVIDIA’s Grace Blackwell Superchip, promising to turbocharge customer and first-party AI offerings. This move signifies a significant step forward in AI infrastructure, offering cutting-edge capabilities for natural language processing, computer vision, and more.

Omniverse and Azure: The collaboration also brings NVIDIA Omniverse Cloud APIs to the Azure ecosystem, facilitating advanced industrial design and simulation tools. This partnership underscores a shared vision to unlock the promise of AI for customers and organizations, paving the way for groundbreaking solutions in various domains

3. Google Cloud and Generative AI: Google Cloud is distinguished by its diverse range of foundation models such as Codey, Chirp, PaLM, and Imagen, which can be utilized and fine-tuned using Vertex AI. The platform integrates seamlessly with Google services, including Google Workspace, and provides no-code tools like Gen App Builder and GenAI Studio for simplified application development. Google Cloud also supports the integration of third-party vector databases for projects requiring vector storage and semantic search, along with robust data analytics capabilities through BigQuery and advanced machine learning resources, making it ideal for complex AI projects .

4. CoreWeave Secures Monumental Funding: Massive Investment: CoreWeave, a prominent player in GPU cloud computing essential for generative AI, has clinched a whopping $642 million in a secondary sale led by Fidelity. This significant cash infusion has catapulted CoreWeave’s valuation to $7 billion. Strategic Growth - This funding round is a testament to CoreWeave’s crucial role in providing the computational power needed by generative AI startups. The company’s focus on renting out Nvidia GPUs in the cloud has made it a go-to resource for AI-driven companies looking for scalable computing solutions .

5. Oracle Enhances Cloud Suite with Generative AI: Oracle announced new generative AI capabilities within its Oracle Fusion Cloud Applications Suite. This enhancement aims to improve decision-making and enrich both employee and customer experiences. By integrating advanced AI features, Oracle is set to offer more comprehensive solutions that leverage the power of cloud and AI technologies .

Expanded Collaboration Focus:

This expanded collaboration between AWS and Anthropic emphasizes AWS’s role as Anthropic’s primary cloud provider. Anthropic will utilize AWS’s specialized AI chips, Trainium and Inferentia, to train and deploy its future foundation models. These chips are designed to provide high-performance, low-cost machine learning accelerators, enabling more efficient development and deployment of generative AI applications. This partnership not only strengthens AWS’s AI capabilities but also ensures that customers have access to cutting-edge, responsibly developed AI models .

This strategic alliance between AWS and Anthropic, supported by Accenture’s integration and customization services, presents a powerful combination of cloud infrastructure and generative AI expertise. It aims to make generative AI more accessible and practical for enterprises, driving innovation and transformation across various industries.

These developments mark a significant period of growth and innovation for the generative AI and cloud computing sector. Companies like Microsoft, NVIDIA, CoreWeave, and Oracle are at the forefront, driving the industry forward with strategic partnerships and investments that promise to unlock new possibilities and efficiencies. As these technologies continue to evolve, we can expect to see even more transformative solutions emerge, reshaping industries and enhancing our interaction with digital environments.

Generative AI Startups:

Few Existing players to watch the space:

1. Uizard Technologies: Based in Copenhagen, Denmark, Uizard offers a collaborative AI design tool that enables non-designers to create software, mobile apps, and websites swiftly .

2. Descript: Located in San Francisco, California, Descript provides a collaborative editor for audio and video that includes transcription, editing, and overdubbing capabilities .

3. Glean: Also based in Palo Alto, California, Glean offers an intuitive work assistant designed to help teams navigate the information overload common in modern work environments .

4. Character.ai: From Menlo Park, California, Character.ai uses neural language models to generate human-like text responses, facilitating contextual conversations through a chatbot web application .

5. Soundraw: A Tokyo-based startup, Soundraw provides an AI-powered platform that enables video creators to generate royalty-free music tailored to their specific needs .

6. AssemblyAI: Located in San Francisco, California, AssemblyAI offers robust AI models for transcribing and understanding speech, accessible through a simple API .

7. Runway: A New York-based applied AI research company, Runway is pioneering the next generation of creativity tools, focusing on video automation and synthetic media .

8. Stability AI: Based in London, UK, Stability AI is designing and implementing open AI tools that transform text commands into images and other forms of media .

9. Anyword: Operating out of New York, New York, Anyword develops content optimization software that uses natural language processing algorithms to unlock audience insights .

10. PromptBase: A London-based startup, PromptBase is a marketplace where users can buy and sell high-quality prompts to enhance the performance of AI models like DALL·E and GPT .

11. Rephrase AI: Acquired by Adobe, Rephrase AI is a text-to-video generation platform allowing users to create videos with selectable video avatars, backgrounds, and voiceovers. .

Note-worthy ones for March 2024:

1. Synthesia: This company is a leader in creating AI-generated videos, making it easier and faster to produce high-quality content.

2. Humanlike: This startup focuses on using generative AI to streamline tasks like invoice processing.

3. Contour: They’re developing next-generation quality assurance tools powered by generative AI, helping businesses improve product testing.

4. Fynt: This startup uses generative AI for autonomous planning and action systems in operational data management. Probably one off – but the website did not respond.

Needless to say OpenAI, Hugging Face, Anthropic, Stability AI, Mid-journey, AI21 Labs are all major forces in Generative AI with strong focus on research and development, they are pushing the boundaries of what is possible with open source and language models.

New Generative AI Models:

Highlighting the most significant Generative AI models released or gained traction in March 2024, categorized by type and focus.

Established Players – Focused on Research & Development:

There weren’t any groundbreaking releases from the major generative AI players like OpenAI, Hugging Face, Anthropic, Stability AI, Midjourney, and AI21 Labs in March 2024 specifically, but these companies are constantly pushing the boundaries in research.

New Models with Specific Applications

1. Adobe’s Generative AI models and creative APIs: Launched in March 2024, these are designed for enterprises to automate content creation and production.

2. AI model for designing new antibiotics (McMaster & Stanford): This model can create billions of potential antibiotic molecules, aiding the fight against superbugs. This isn’t a general-purpose generative model, but a significant advancement in a specific field.

3. Databricks DBRX: This open-source large language model (LLM) is designed to be efficient and outperform other open-source models on standard benchmarks. It’s also built for customization.

Advancements from Existing Players:

AI21 Labs’ next generation of Summarize Conversation: This uses a new Task-Specific Model to automatically summarize conversations, improving accuracy. This isn’t necessarily a completely new model, but a significant update to an existing tool.

Generative AI & Leaders in News:

While weren’t any earth-shattering breakthroughs in generative AI research specifically tied to March 2024, there was still significant movement in the field. Here’s a breakdown of generative AI and its leaders in the news for March 2024.

Generative AI Leaders in the News:

Microsoft Ireland & Trinity College Dublin: Released a report highlighting Ireland’s potential as a generative AI leader.

AI21 Labs: Launched the next generation of Summarize Conversation.

Databricks Mosaic Research team: Released the open-source Databricks DBRX LLM. IMHO, Databricks is giving a moment of “Who Moved my Cheese” to the other major players! For this month, this news is supremely well played and note-worthy.

Amazon invests USD $ 2.75 Billion more in AI Startup Anthropic. WSJ Link

Studies and Reports:

Udemy: Conducted a study highlighting a gap between employee and executive readiness for generative AI leadership

Generative AI and Government / Policy Makers:

These were significant discussions and policy moves regarding generative AI in March 2024, with a focus on responsible implementation:

1. The White House issued a memorandum (M-24–10) on March 28th, 2024. It emphasized “Advancing Responsible AI Innovation” within the US Federal Government. This memo encouraged agencies to adopt AI responsibly, including generative AI, with safeguards in place.

2. The European Union continued discussions around the AI Act throughout March 2024. This proposed legislation aims to be the first legal framework governing AI, addressing risks and ethical considerations. The European Union agreed on the AI Act, setting a global precedent with comprehensive laws tailored to generative AI. This landmark regulation delineates clear standards for foundation models and high-risk applications in sensitive sectors like healthcare and education. It emphasizes transparency in model development and holds companies accountable for any resulting harms. The AI Act particularly targets high-risk AI systems, demanding that such systems are trained on representative data sets to minimize biases. Moreover, it places strict limitations on AI uses that pose significant threats to fundamental rights, including the prohibition of facial recognition databases in public spaces without court approval. This legislative framework is poised to shape global AI standards, underscoring the EU’s proactive stance on digital ethics and citizen protection .

3. India’s Ministry of Electronics and Information Technology (MeitY) issued advisories in March. On March 1st, they required permission for launching some generative AI models, particularly those under development. A later advisory in March emphasized clear labeling for user awareness of potential inaccuracies.

4. China: Navigating Fragmented AI Regulation – China’s approach to AI regulation remains fragmented, targeting specific AI advancements with individual legislation. However, a comprehensive “artificial intelligence law” is on the legislative agenda, indicating a shift towards more holistic governance. This proposed law suggests the establishment of a national AI office and mandates yearly “social responsibility reports” for foundation models, aiming to exert tighter control over the generative AI landscape. Currently, foundation models in China require government registration, reflecting the country’s stringent regulatory environment .

5. United States: FTC’s Assertive Stance on AI Regulation – The Federal Trade Commission (FTC) has positioned itself as a key regulator for AI, expressing intentions to regulate generative AI technologies assertively. It critiques the previous era’s self-regulation model and emphasizes the use of existing laws to address AI-induced harms. The FTC advocates for market fairness, proactive enforcement against deceptive AI practices, and the establishment of comprehensive rules to mitigate AI-related harms. This includes initiatives like the “Impersonator Rule,” aiming to combat fraud through advanced technologies like voice-cloning. The FTC’s proactive approach signals a significant regulatory push in the US to safeguard consumers against the potential risks posed by AI .

6. Global Perspectives: Generative AI in Government Operations – Across the globe, generative AI is transforming government operations, promising enhanced efficiency and innovation while posing new challenges. Governments are employing generative AI for various applications, from administrative streamlining to cybersecurity, necessitating robust governance frameworks to ensure ethical, transparent human-AI collaboration. Concerns about biased service delivery, data security, and misinformation highlight the need for comprehensive risk management strategies in the deployment of generative AI technologies.

Generative AI and Job market:

The market in March 2024 was experiencing a period of adjustment due to generative AI, with both potential job displacement and creation.

Job Displacement:

Certain professions faced increased pressure: Jobs in repetitive tasks, data analysis, and specific creative fields like graphic design were susceptible to automation by generative AI.

Shifting skillsets: While some jobs might be replaced entirely, others would require workers to adapt and develop new skillsets to work alongside generative AI tools effectively.

Job Creation:

Rise in AI-related jobs: There was a significant increase in job postings seeking skills related to developing, managing, and utilizing generative AI tools. Software development and data science were particularly in demand for generative AI tasks.

New job roles: New job roles emerged that focused on tasks like training generative AI models, ensuring data quality, and overseeing ethical implementation.

Overall Trend:

Analysts predicted a long-term transformation rather than a sudden mass unemployment crisis.

The focus was on worker retraining and adaptation to remain competitive in the changing job market.

Here are some resources for further reading:

2024: Year of Keeping ‘an AI’ on Job Disruptions [ALiTech, alitech.io] discusses potential job disruptions caused by AI.

AI’s Growing Impact: Transforming the Job Market in 2024 and Beyond [Signature Recruitment, signaturerecruitment.co.uk] explores the impact of AI on various industries.

AI will fundamentally transform the job market but the risk of mass unemployment is low [ING Think, think.ing.com] provides a balanced perspective on AI and job markets.

Remember, the generative AI field is constantly evolving, so the job market landscape will likely continue to change.

Noteworthy news I read and enjoyed: https://www.wsj.com/tech/ai/the-fight-for-ai-talent-pay-million-dollar-packages-and-buy-whole-teams-c370de2b