End of 2023: Notable AI Events in AI and Emerging LLM Developers

At the end of 2023, the AI landscape was marked by several significant advancements, new players, and transformative applications. As the CEO of Conversica, leader in Conversational Automation for revenue teams, I am definitely navigating an exciting era of innovation. Here are some key events and trends in AI for the year, 2023:

Notable AI Events in 2023

1. Advancements in Generative AI:
The capabilities of generative AI models (OpenAI GPT, Google Gemini, Meta AI, Microsoft Azure AI, AWS AI, Mistral AI, Cohere, Anthropic AI) continued to improve, leading to more sophisticated and creative applications in art, music, writing, and design. New techniques in generative adversarial networks (GANs) and transformer architectures enable AI to produce highly realistic and contextually relevant content.

2. AI in Healthcare:
AI’s role in healthcare expanded with breakthroughs in predictive analytics, personalized medicine, and diagnostic tools. AI models improved the accuracy of early disease detection, optimized treatment plans based on patient data, and assisted in drug discovery, reducing the time and cost of bringing new treatments to market.

3. AI Ethics and Regulation:
Regulatory bodies and organizations worldwide advance their efforts to create frameworks for ethical AI. The European Union’s AI Act moves closer to implementation, setting standards for AI transparency, accountability, and bias mitigation. The US (see state regulations here, or DOD here) and other countries also develop their own regulatory approaches to ensure the responsible use of AI.

4. Climate Change and Environmental Monitoring:
AI technologies continued to play a critical role in addressing climate change. AI models are used for climate predictions, optimizing renewable energy systems, and monitoring environmental changes. These applications help in developing more effective strategies for mitigating and adapting to climate change. But equally as important is answering the question, “how do we power all this AI technology?”. Green AI is going to become a real area of interest very soon.

5. AI in Autonomous Systems:
Significant progress was made in autonomous systems, including self-driving cars, drones, and robotics. AI algorithms improve the safety, reliability, and efficiency of these systems, leading to wider adoption in logistics, transportation, and other industries.

6. Natural Language Processing (NLP):
NLP technologies saw further advancements this year with the release of more powerful and efficient language models. These models enhance AI’s ability to understand and generate human language, leading to better performance in applications such as chatbots, virtual assistants, and translation services.

For Conversica, we focused advanced AI technologies (specifically vector search, GPT-4, and Llama2) on developing an enterprise-class solution for chat (knowing it would soon be disrupted and commoditized). We strategically focused on “up-market” enterprises, knowing that the long-tail would be saturated with GPT-powered chat solutions. However, a enterprise solution couldn’t really be released to highly regulated industries until now (think banking). GPT-2 in 2020, was maybe 40% accurate for our enterprise brands. In 2021, GPT-3 got us to 60% accuracy. In 2022, we were able to tune our models for clients to achieve 85% accuracy. Now, with the release of GPT-3.5 turbo, and then GPT-4, our path to near-100% accuracy for enterprise clients can be achieved, especially using RAG as a design pattern. Now the Fortune 100 are within reach, for the first time.

Traditional Chatbots developed by companies like Drift, Intercom, and over 20 others are dead. We’re now moving from a chatbot into a virtual agent. Solutions like OpenAI ChatGPT, Google Gemini, Microsoft Co-Pilot, Meta AI, Anthropic Claude, all allow the layman to understand what is possible, AND what to expect. The genAI-enabled agent wars have begun, and the bar has been raised for the next-gen version of the chatbot.

Emerging LLM Developers and New Players in 2023

1. Mistral AI:
Founded in March 2023, Mistral AI focused on developing large-scale language models for environmental monitoring and climate science. Their models analyzed vast datasets to provide accurate climate predictions and support sustainable practices.

2. Cohere:
Cohere, founded in 2019, continued to make strides in providing NLP as a service, offering advanced language models that could be easily integrated into various applications. Their focus on accessibility and usability made them a key player in the commercial application of LLMs.

3. Anthropic AI:
Anthropic AI, founded in 2021, established by former OpenAI employees, prioritized the development of interpretable and safe AI systems. Their research focused on creating LLMs that were not only powerful but also aligned with human values and safety standards.

4. Inflection AI:
Inflection AI, founded in 2022, another new entrant, aimed to create AI systems that enhance human-computer interactions. Their models focused on improving the quality of conversations between humans and AI, making digital interactions more natural and effective.

5. EleutherAI:
EleutherAI, founded in 2020, a collective of researchers committed to open-source AI research, released several large language models in 2023. Their focus on transparency and collaboration contributed to the broader AI research community by providing accessible, high-quality models.

6. Grok AI:
Grok AI, founded in 2022 and announced in 2023, gained traction with its AI-powered code review and documentation platform. Their tools helped software developers maintain high-quality codebases and streamline their development workflows.

In 2023, the AI field was characterized by rapid advancements by existing players, mostly, and some new players, and a strong focus on ethical and responsible AI development. As the CEO of Conversica, I am at the helm of a dynamic industry, leveraging these innovations to drive growth and deliver cutting-edge solutions to our clients. This is arguably the fastest growing technology in the history of tech.

More on Advancements in Generative AI in 2023

Generative AI continued to advance rapidly, with significant breakthroughs and applications across various domains. These advancements enhanced the capabilities of AI models to create realistic and contextually relevant content, opening new possibilities in art, music, writing, and more. Here are some key developments in generative AI during the year:

1. Enhanced Model Architectures:
Researchers developed more sophisticated architectures for generative models, such as improved versions of GANs (Generative Adversarial Networks) and transformers. These models were more efficient, produced higher quality outputs, and required less computational power.

2. Multimodal Generative Models:
The integration of multimodal capabilities became more prominent, with models able to generate and understand text, images, audio, and video. This allowed for more cohesive and context-aware generation across different media types.

3. Improved Text Generation:
Large language models like GPT-4 and other advancements in NLP made text generation more coherent, contextually accurate, and human-like. These models were used in applications ranging from chatbots to creative writing and automated content creation.

4. Creative AI in Art and Music:
AI-driven tools for generating visual art and music saw significant improvements. Artists used these tools to explore new creative possibilities, blending human creativity with machine-generated suggestions. AI-generated art and music gained popularity in both digital and physical forms.

5. AI-Driven Content Creation:
Generative AI was increasingly used for automated content creation in marketing, entertainment, and education. AI tools generated high-quality articles, reports, social media posts, and video scripts, reducing the time and effort required for content production.

6. Real-Time Generative AI:
Real-time generative AI applications became more viable, enabling interactive experiences in gaming, virtual reality (VR), and augmented reality (AR). These applications provided dynamic and immersive environments that responded to user inputs in real-time.

7. Ethical and Bias Mitigation Efforts:
Researchers and developers focused on addressing ethical concerns and biases in generative AI models. Techniques for ensuring fairness, transparency, and accountability were integrated into the development and deployment processes, aiming to create more responsible AI systems.

8. AI in Film and Animation:
Generative AI began to play a significant role in film and animation production, from generating storyboards and scripts to creating realistic special effects and character animations. These tools streamlined the creative process and allowed for greater experimentation.

9. Fashion and Design:
AI tools for fashion and design evolved, enabling designers to generate new clothing patterns, accessories, and even virtual fashion shows. Generative AI assisted in predicting fashion trends and creating customized designs based on user preferences.

10. Healthcare Applications:
In healthcare, generative AI was used to create synthetic medical data for training purposes, design new drugs, and generate personalized treatment plans. These applications helped accelerate medical research and improve patient outcomes.

Notable AI Applications and Tools in 2023

1. DALL-E 3:
OpenAI released DALL-E 3, a powerful image generation model that created highly detailed and contextually appropriate images from textual descriptions. This model was used in various creative and commercial applications.

2. MuseNet 2.0:
MuseNet 2.0, an updated version of OpenAI’s music generation model, offered enhanced capabilities for composing music across multiple genres and styles. Musicians and producers used it to generate innovative compositions and experiment with new sounds.

3. RunwayML:
RunwayML continued to provide accessible tools for artists and creators, integrating the latest generative models into their platform. Users could easily apply AI to their creative projects, from visual art to interactive media.

Notable Company Moves in AI in 2023

Adobe & AI in 2023

1. Adobe Sensei Enhancements:
Adobe introduced significant enhancements to Adobe Sensei, its AI and machine learning platform. The updates focused on improving creative tools across Adobe’s suite of products, including Photoshop, Illustrator, and Premiere Pro. New features included more powerful AI-driven image and video editing tools, automated content generation, and enhanced design suggestions.

2. Generative AI for Creative Cloud:
Adobe integrated generative AI capabilities into Creative Cloud, allowing users to generate high-quality images, graphics, and designs from text prompts. This feature, known as Adobe Firefly, enabled creative professionals to streamline their workflows and experiment with new creative possibilities.

3. AI-Powered Marketing Tools:
Adobe expanded its AI-driven marketing solutions within Adobe Experience Cloud. These tools provided advanced customer segmentation, predictive analytics, and personalized content recommendations, helping marketers deliver more effective and targeted campaigns.

4. Adobe Analytics with AI Insights:
Adobe Analytics received updates to include deeper AI-driven insights and predictions. This allowed businesses to better understand customer behavior, optimize their marketing strategies, and improve decision-making processes based on real-time data analysis.

Amazon Web Services (AWS) and AI in 2023

1. Amazon SageMaker Updates:
AWS introduced new features and enhancements to Amazon SageMaker, its machine learning service. The updates included improved tools for model training, deployment, and monitoring, making it easier for developers to build and manage machine learning models at scale.

2. AI-Powered AWS Services:
AWS expanded its portfolio of AI-powered services, including new offerings for natural language processing, computer vision, and automated customer service. Services like Amazon Comprehend and Amazon Rekognition received upgrades to enhance their accuracy and capabilities.

3. AWS HealthLake AI:
AWS launched new AI features for AWS HealthLake, a service designed to store, transform, and analyze health data. The updates included advanced analytics and machine learning capabilities to help healthcare organizations derive insights from medical records and improve patient care.

4. AI for Sustainability:
AWS announced AI initiatives focused on sustainability, including tools to optimize energy usage in data centers and support environmental research. These efforts aimed to help organizations reduce their carbon footprint and promote sustainable practices.

Google & AI in 2023

1. Google PaLM Expansion:
Google expanded its Pathways Language Model (PaLM) with new capabilities and applications. PaLM was integrated into various Google services, enhancing search, translation, and conversational AI. The model’s ability to understand and generate human language was further improved, making interactions more natural and contextually aware.

2. AI-Powered Google Workspace:
Google introduced AI-driven features in Google Workspace to boost productivity and collaboration. New tools included smart scheduling, automated meeting summaries, and advanced document editing capabilities powered by AI.

3. Google Cloud AI Updates:
Google Cloud announced new AI and machine learning services, including Vertex AI enhancements for building, deploying, and scaling machine learning models. The updates aimed to make AI more accessible to enterprises and developers, enabling them to leverage Google’s advanced AI technologies.

4. Ethical AI and Responsible AI Initiatives:
Google reinforced its commitment to ethical AI with new initiatives and guidelines to ensure the responsible development and deployment of AI technologies. This included efforts to address bias, improve transparency, and promote fairness in AI systems.

Microsoft & AI in 2023

1. Microsoft Azure AI Advancements:
Microsoft introduced several updates to Azure AI, its suite of AI services and tools. These included new machine learning capabilities, enhanced natural language processing features, and improved tools for building and deploying AI models.

2. AI Integration in Microsoft 365:
Microsoft integrated AI-powered features into Microsoft 365, enhancing productivity tools such as Word, Excel, and Outlook. These features included advanced writing suggestions, data analysis, and automated email responses, making everyday tasks more efficient.

3. Azure OpenAI Service:
Microsoft expanded its Azure OpenAI Service, providing broader access to OpenAI’s models, including GPT-4. This service allowed businesses to integrate powerful language models into their applications, enabling advanced conversational AI and text generation capabilities.

4. AI for Good Initiatives:
Microsoft continued to invest in AI for Good initiatives, focusing on using AI to address societal challenges. This included projects aimed at improving accessibility, supporting education, and promoting sustainability through AI-driven solutions.

These announcements from Adobe, AWS, Google, and Microsoft in 2023 highlighted their ongoing commitment to advancing AI technologies and integrating AI into a wide range of products and services. These developments aimed to enhance user experiences, drive innovation, and address global challenges through the power of AI.

Some Salesforce & AI in 2023

In 2023, Salesforce continued to innovate and expand its suite of AI-powered tools and services, solidifying its position as a leader in customer relationship management (CRM) and enterprise cloud computing. Here are some notable announcements and advancements from Salesforce in 2023:

1. Salesforce Einstein GPT:
Salesforce announced the integration of generative AI capabilities into its Einstein platform, branding it as “Einstein GPT.” This new feature leverages advanced language models to provide more sophisticated AI-driven insights, predictive analytics, and automation across Salesforce’s various products. Einstein GPT aimed to help businesses enhance customer interactions, automate routine tasks, and derive actionable insights from vast amounts of data.

2. Salesforce Genie:
Salesforce introduced Salesforce Genie, a real-time data platform that helps organizations unify and act on customer data from various sources. Genie integrates seamlessly with Salesforce’s CRM tools, providing real-time insights and enabling more personalized customer experiences. This platform is designed to handle large-scale data and support the growing demand for real-time analytics and decision-making.

3. Salesforce Net Zero Cloud Enhancements:
Building on its commitment to sustainability, Salesforce announced significant enhancements to its Net Zero Cloud. These updates included more robust data analytics and reporting features to help companies track and reduce their carbon emissions. Salesforce also introduced new partnerships and integrations with leading sustainability data providers, further empowering businesses to meet their environmental goals.

4. Einstein for Healthcare:
Salesforce expanded its Einstein capabilities specifically for the healthcare sector. This included AI-driven tools for patient data analysis, personalized care recommendations, and streamlined administrative processes. The aim was to improve patient outcomes, enhance operational efficiency, and support healthcare providers in delivering high-quality care.

5. AI-Powered Marketing Cloud Innovations:
Salesforce unveiled new AI-driven features for its Marketing Cloud, designed to enhance customer engagement and marketing effectiveness. These included advanced segmentation tools, predictive analytics for campaign optimization, and generative AI for personalized content creation. These innovations aimed to help marketers deliver more targeted and impactful campaigns.

6. Tableau GPT:
Salesforce integrated GPT-powered analytics into Tableau, its data visualization and business intelligence platform. Tableau GPT enabled users to generate natural language insights from complex datasets, making data analysis more accessible and intuitive. This feature allowed users to ask questions and receive detailed, AI-generated responses directly within Tableau.

7. MuleSoft AI Integrations:
Salesforce announced AI-powered enhancements to MuleSoft, its integration platform. These updates included intelligent data mapping, automated workflow creation, and predictive analytics to optimize data flows across enterprise systems. MuleSoft AI aimed to simplify complex integrations and improve data consistency and accuracy.

8. Enhanced Security and Compliance Features:
To address growing concerns around data privacy and security, Salesforce introduced new AI-driven security and compliance features. These included advanced threat detection, automated compliance reporting, and enhanced data encryption. Salesforce’s commitment to security aimed to provide businesses with the tools needed to protect their data and comply with regulatory requirements.

These announcements and advancements from Salesforce in 2023 demonstrated the company’s commitment to leveraging AI to drive innovation, improve customer experiences, and support sustainable business practices. Salesforce’s focus on integrating advanced AI technologies across its platform ensured that businesses could harness the full potential of AI to achieve their goals.


Jim Kaskade

Jim Kaskade is a serial entrepreneur & enterprise software executive of over 36 years. He is the CEO of Conversica, a leader in Augmented Workforce solutions that help clients attract, acquire, and grow end-customers. He most recently successfully exited a PE-backed SaaS company, Janrain, in the digital identity security space. Prior to identity, he led a digital application business of over 7,000 people ($1B). Prior to that he led a big data & analytics business of over 1,000 ($250M). He was the CEO of a Big Data Cloud company ($50M); was an EIR at PARC (the Bell Labs of Silicon Valley) which resulted in a spinout of an AML AI company; led two separate private cloud software startups; founded of one of the most advanced digital video SaaS companies delivering online and wireless solutions to over 10,000 enterprises; and was involved with three semiconductor startups (two of which he founded, one of which he sold). He started his career engineering massively parallel processing datacenter applications. Jim has an Electrical and Computer Science Engineering degree from University of California, Santa Barbara, with an emphasis in semiconductor design and computer science; and an MBA from the University of San Diego with an emphasis in entrepreneurship and finance.