The AI Players for Marketers:Landscape September 2023
More than 7,000 new AI tools were released between January and August 2023, and most marketers have embraced AI in some form. But as our industry evolves, it’s not always easy to keep up with all the latest developments.
Who’s Shaping the World of AI Marketing Tools?
Market cap: $2.46T
Solidified its position as global AI leader with a $10B investment in OpenAI and integration of ChatGPT and Dall-E into its search engine and web browser
Market cap: $1.57T
Acquired DeepMind Technologies in 2014, formed the Google AI division in 2017, launched its AI chatbot Bard in 2023, and has debuted AI photo editing and search experiences
Valuation: $30B
Now ranked among the 10 largest unicorn startups, the company behind ChatGPT and Dall-E began as a non-profit in 2015 but has attracted investments from the likes of Microsoft, Elon Musk, and AWS
Valuation: $4.1B
10% owned by Google, raised $450 million in a May funding round, and has focused on safe, responsible AI use as it develops Claude, a ChatGPT competitor that is being integrated into Slack and Zoom
Market cap: $788.15B
Released its Llama 2 AI model earlier this year, and has announced work on an advanced platform it says will rival OpenAI capabilities
Market cap: $123.87B
Its Watson question-answering platform won Jeopardy! in 2011, bringing attention to AI language models, and has twice been recognized as a conversational AI leader by Gartner
The Tech Behind the Tools
ANNs
Generative AI tools are built on artificial neural networks, a type of machine learning process that teaches computers to process data in a way that is inspired by the human brain, allowing them to “learn.” This adaptive system lets computers continuously improve to mimic the content they’re trained on and, eventually, solve complex problems and create original content.
LLMs
Large language models — the technology behind text-based generative AI tools, are a type of ANN. Foundation models — LLMs so large and impactful they serve as a base for optimization and refinement — include:
- OpenAI’s GPT-4
- Google’s PaLM
- Meta’s LLaMA
Open-Source vs. Proprietary Models
Most of the major players in the AI industry are developing proprietary models, but open-source models — which draw on the collaborative expertise of anyone interested — are quickly gaining ground, experts say.
Open-Source
PROS
- Freely distributed
- Best for flexibility and transparency
CONS
- Can require more resources to fine-tune
- Typically slower to market
- Often lacks security and governance capabilities
Proprietary
PROS
- Shorter time to market
- Can include added security and governance capabilities
CONS
- Usage-based fees
- Fine-tuning can incur additional costs
- Limited or no transparency into code
Which Tools Are Marketers Using?
A Data-Driven Approach to AI in Marketing
At TPM, we’re always looking for new tools and strategies that can help us improve our clients’ marketing efforts. We’ve launched a series of experiments to help us identify where AI marketing tools can augment or replace human efforts and where the technology isn’t quite there yet. Check out our progress or contact us to learn more.
