10 AI Predictions For 2023Sachin Kalaskar
1. GPT-4 is Coming
GPT-4 brings improved natural language understanding, more accurate text generation, advanced language translation, increased pattern recognition, ability to perform multiple NLP tasks, new possibilities for NLP research and development, and more accurate results in industries relying on NLP like chatbots, virtual assistants and content generation.
2. Data Constraints on Language Models
Data constraints could limit the further development of language models as they require more data to improve. Limitations include overfitting, the high cost of data collection, and privacy concerns. To overcome these, researchers and engineers must find ways to work with limited data through efficient data collection methods and utilizing smaller data sets effectively.
3. Driverless Cars
Autonomous vehicles are becoming increasingly advanced, and we are now at the stage where fully driverless cars are becoming a reality. These cars will not require human input and can transport people safely and efficiently without human intervention. Some customers will begin using these cars for their everyday transportation needs.
Startup Midjourney will raise venture capital to expand operations, develop products, grow and scale, increasing market presence and improving chances of success.
5. AI-Enabled Search
The search landscape is shifting towards more conversational and personalized, utilizing AI and machine learning to understand user intent and context. It would be a more significant change than what happened since Google became popular in the early 2000s.
6. Humanoid Robots
Humanoid robot development is gaining increased attention, funding, talent, and new projects launching to improve capabilities, making them more human-like and ready for a broader range of tasks.
7. Emergence of LLMOps
LLMOps, a new trend in MLOps, focuses on the challenges of deploying, maintaining, and monitoring large language models and will gain more attention and usage.
8. AlphaFold is Set to Rise
AlphaFold is a deep-learning-based protein structure prediction system that has made significant breakthroughs in bioinformatics. Due to its accuracy and success, more and more research projects in bioinformatics will likely build upon or cite AlphaFold.
9. DeepMind, Google Brain, and OpenAI
DeepMind, Google Brain, and OpenAI are all renowned research organizations in the field of AI, working towards building a foundation model for Robotics, which would have a broad range of capabilities, including object recognition, navigation, manipulation, and decision-making. This model would serve as a foundation for more advanced robotic systems and improve its overall performance.
10. US Chip Manufacturing to Boost
The US will invest billions in new chip manufacturing facilities as a contingency plan against supply chain disruption from Taiwan to increase domestic production and secure the supply chain.