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The power and uncertainty of probabilistic AI

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May 1, 2024

In our daily lives, certainty can oftentimes feel like a luxury.

We navigate through our days based on probabilities, making decisions with the hope of reaching our goals despite inevitable surprises.

Though we yearn for determinism, our world fundamentally operates under probabilistic rules, filled with unpredictability and chance.

This same principle applies to the development and function of artificial intelligence (AI), especially in the domain of probabilistic AI.

Probabilistic AI
Probabilistic AI excels in managing uncertainty by predicting a range of possible outcomes, each assigned a certain likelihood.

This contrasts with deterministic models, which provide fixed results from specific inputs.

In unpredictable or ambiguous environments, probabilistic models adapt by considering various potential scenarios, thereby offering more nuanced responses than their deterministic counterparts.

These models are not just theoretical constructs – they underpin many of the AI systems we use daily, including large language models (LLMs) that predict text and handle linguistic uncertainties.

Real-world comparison
To illustrate, let’s compare responses from Google’s search engine and an LLM to an ambiguous query involving Green Bay football knowledge: “In 2024, which Mondays will hold Packer worship services?”

Google search – Response 1:
Four YouTube videos of church services from 2024People also asked:What is the longest night of the year worship service?What day do people usually go to religious services?Position 1-4: More church worship schedules5th position: Lambeau Field Stadium Tours
Google search – Response 2: Same output
Google’s search algorithm, being more deterministic, yields static results focused on keyword relevancy and consistency, such as videos of church services and stadium tours.

On the other hand, an LLM provides a more nuanced understanding, recognizing the playful connotation behind “Packer worship services” and offering a creative interpretation related to Green Bay Packers fan events on NFL game days.

LLM Response 1:
It seems like you’re asking about the schedule for a specific event or service, possibly related to the Green Bay Packers.
If this is about actual worship services or events connected to fan activities for the Packers, I’d need a bit more context to provide accurate information.
Could you clarify if you’re referring to a specific kind of event or location where these services or gatherings occur?
If it’s a fun or fictional concept, let me know how you’d like to explore it.

LLM Response 2:
“Packer worship services” sounds like it might be a playful way of referring to events or gatherings for fans of the Green Bay Packers, possibly on game days or other special occasions. In the context of football, fans might “worship” their team on game days, which often fall on Mondays during the NFL’s “Monday Night Football.”
Here are the Monday dates during the NFL regular season in 2024 when the Green Bay Packers might have games, and thus when fans might gather for these metaphorical “worship services:”
September 2024: Monday games can occur starting from the first week of the NFL season, which typically begins in early September.October to December 2024: Monday night games continue throughout these months.To find out specific dates when the Packers are playing on Mondays, you would need to check the NFL schedule for the 2024 season or updates from the team about their game days.
This would give you the exact Mondays when Packers’ fans might be engaging in their version of “services” by watching the game and cheering for their team.

Advantages of probabilistic AI
This example highlights several advantages of probabilistic AI:
Flexibility and adaptability: It can generate multiple potential outcomes and infer underlying meanings, making it highly adaptable in diverse scenarios.Alignment with human decision-making: Probabilistic AI mimics human reasoning processes, which often rely on assessing probabilities rather than certainties, thus providing responses that feel more natural and intuitive.
Appreciating, managing AI hallucinations, variability
Understanding the probabilistic nature of AI helps in appreciating its variability and the occasional “hallucinations” (incorrect or nonsensical responses).

Also, AI systems are equipped with mechanisms allowing engineers and users to adjust the level of variability in responses.

This adjustability enables AI to cater to a wide range of scenarios, from highly creative tasks requiring diverse outputs to more controlled environments where consistency is crucial.

Cautions and considerations
Despite its advantages, probabilistic AI is not without its limitations:
Not all use cases benefit from probability: There are contexts where deterministic results are preferable, such as applications requiring precise and consistent outcomes. Making a probabilistic AI respond deterministically is possible but may be going about the solution of a use case in the wrong way, especially if you are looking for a repeatable and long-term solution.Probability is Imperfect by design: Users need to maintain realistic expectations about the capabilities and limitations of probabilistic AI systems, understanding that while they offer significant flexibility, they are not perfect – just like us and the real world.
Probabilistic AI reflects the complex nature of our real-world environments and decision-making processes.

As we continue to integrate AI into various sectors, it is crucial to recognize both its potential and its boundaries.

By fostering a balanced appreciation and understanding of probabilistic models, we can better harness their capabilities while also advocating for responsible use and thoughtful discussions around their broader implications.

This approach will help ensure we remain informed and cautious as we navigate the evolving landscape of artificial intelligence.

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