AI Advances Across Industries - From Investing to Robots, Marketing to Math
AI Advances Across Industries - From Investing to Robots, Marketing to Math: Optimizing the Future with Cutting-Edge Technology
Promising AI Stocks Trading at Steep Discounts
- Palantir stock down 54% provides data analytics software, grew revenue from $595M to $1.9B
- Becoming profitable, swung from $623M operating loss to $40M income
- Smartsheet stock down 47% offers AI project management software
- Subscription revenue up 23% last quarter
- Both benefit from surging AI demand and are discounted buys
Tapping into AI to Create Future Experiential Marketing
- AI infiltrating digital marketing, but potential in experiential remains untapped
- Eventually enable more immersive, personalized physical brand experiences
- Start now by using AI for creative inspiration and post-event consumer sentiment analysis
- Build composable solutions combining traditional methods with emerging AI tools
- Create complementary virtual environments with affordable metaverse-building AI
Major Advances Signal Imminent Rise of Useful Robots
- Specialized robots giving way to more general intelligence like language model-controlled navigation
- DeepMind's Eureka enables autonomous improvement of robot training
- Nvidia simulations empower rapid experimentation
- Together enabling capable, general-purpose robots soon commercially
- Tesla's Optimus may leverage similar breakthroughs given rapid development
- Like chatbot explosion in 2022, robot proliferation may hit inflection point in 2024
Unlocking Mathematical Discovery with Language Models
- FunSearch pairs creative LLM proposing solutions in code with evaluator guarding against errors
- By iterating between them, initial code "evolves" into new publishable discoveries
- Found larger cap sets for renowned open problem than prior 20 years of work
- Discovered more efficient algorithms for ubiquitous bin packing problem
- Reveals constructed code for scientists to understand and extend solutions
- Powerful new paradigm in AI-assisted research by selectively expanding on LLM's most promising ideas
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Major Advances Signal Imminent Rise of Useful Robots
Recent announcements from Tesla about its humanoid Optimus robot and other AI developments signal a seismic shift in robotics. For years, robots made incremental improvements but remained limited to specialized, pre-scripted tasks. Now new approaches are enabling more general intelligence in robotics.
Google's robotic Transformer model pilots robots by following natural language commands, using vision and language skills learned from the web. DeepMind’s Eureka system allows AI to autonomously develop better reward functions for training robots in simulations, eventually surpassing human designers. And Nvidia simulations empower rapid robotic experimentation.
Together, these innovations enable AI to control and improve robots with little human input. Much like AlphaGo’s move 37, the AI solutions often seem counterintuitive to humans at first, but prove more effective. Within a year, the advances could yield capable, general-purpose robots appearing commercially.
Tesla may be leveraging similar breakthroughs for its Optimus prototype. The impressive video reveals advanced mobility, suggesting that pre-trained models and simulations hastened development. And subtle design choices like off-center leaning evoke human-like imperfection.
As with the recent explosion of chatbots in 2022, robotic capabilities may soon transition from theoretical to practical. The field could hit an inflection point in 2024 where capable robots proliferate businesses and households. So while physical constraints slow robotic adoption versus software, swift progress in algorithms and simulations primes robotics for its biggest leap yet across the coming year.
2 Artificial Intelligence (AI) Stocks Down 46.5% and 54% to Buy Now
Promising AI Stocks Trading at Steep Discounts
Palantir Technologies and Smartsheet are two artificial intelligence (AI) stocks that look attractive after substantial sell-offs. Palantir provides data analytics software and has grown revenue from $595 million in 2018 to $1.9 billion in 2022. It is becoming profitable, swinging from a $623 million operating loss in 2018 to $40 million in operating income last quarter. The stock is down 54% from its high. Smartsheet offers AI-powered project management software, with subscription revenue up 23% last quarter. Its stock is down 46.5% from its peak. Both companies are benefiting from surging AI adoption. Though not cheap, if AI demand continues growing rapidly, these discounted stocks could deliver strong returns. The Motley Fool contributors making the case argue now looks like a good time to start building positions.
Tapping into AI to Create Future Experiential Marketing
While AI has begun infiltrating digital marketing, its potential in experiential marketing remains relatively untapped. However, AI tools for physical events will emerge to help create more immersive, personalized experiences, optimize events, and justify budgets.
Brands can start laying the groundwork now in three key ways. First, use current AI for inspiration on copy, content, and creative ideas to inform event approaches. Eventually AI can help gather qualitative post-event consumer sentiment from various sources. Second, create composable solutions harnessing traditional experience with various AI tools for customization. With many new tools emerging, differentiation will come from effectively combining them. Finally, build complementary virtual environments using AI tools like Atlas to render physical spaces into affordable metaverse extensions.
Though AI cannot yet fully execute events, substantial opportunities exist to establish a strong foundation and evolve offerings. By preparing now with basic applications, inspiration sources, composable solutions across tools, and virtual complements, brands can lead the next wave of experiential marketing powered by future AI capabilities. The human touch remains indispensable, but out-of-home experiences will evolve exponentially when AI unlocks more immersive, data-driven customization.
Unlocking Mathematical Discovery with Language Models
Researchers have introduced FunSearch, the first method enabling large language models (LLMs) to make verifiable new discoveries in mathematics and computer science. FunSearch pairs a creative LLM proposing solutions in code with an evaluator guarding against errors. By iterating between these components, initial code "evolves" into publishable knowledge.
On the renowned open problem of determining cap sets in combinatorics, FunSearch found larger cap sets than prior human-driven techniques over 20 years of work. And for the ubiquitous bin packing problem, it discovered more efficient algorithms.
Beyond simply outputting solutions, FunSearch reveals the constructed code. This allows scientists to understand and build upon the LLM's problem-solving approach, enabling further collaborative advances.
By selectively expanding on an LLM's most promising ideas within a critical feedback loop, FunSearch unlocks LLMs' immense creativity for mathematical research. The system represents a powerful new paradigm in AI-assisted discovery. Its code-centered technique allows efficiently verifying solutions while transparently conveying the construction logic. FunSearch highlights the vast, untapped potential of language models to comprehensively explore complex search spaces and drive scientific progress through human-AI collaboration.
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