The Future of Search and AI

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The document discusses current and upcoming trends in search and AI. It notes that large datasets are less important than actionable intelligence. Assistive search using personalization, voice, images, conversations, context and providing answers and actions rather than just links is the new paradigm. The future of search and AI involves driving relevant interactions and experiences for customers through digital moments.

Technologie

The Future of Search & AI
Trey Grainger
SVP of Engineering, Lucidworks
@treygrainger
#Activate18 #ActivateSearch

So what are the current and  
upcoming trends in Search & AI?

We need big answers.
Because we don’t need “big data.”

And that mass adoption of LTR looks like this..

But what about all the other aspects
of Search beyond AI?

relevance, scale, bm25, user experience, learning to rank,
autoscaling, sys admin, server provisioning, lemmatization/stemming,
cloud, docker, aws, natural language processing, etl, entity extraction,
tf-idf, phrase detection, semantic search, query pipelines, connectors,
web crawling, signals, real-time recommendations, personalization,
question answering, request handlers, search components,
autocomplete, spell checking, synonyms, stop words, query-log
mining, probabilistic query parsing, boolean queries, geo-spatial
queries, image search, voice search, classification models, bi-
directional cross-datacenter replication, semantic knowledge graphs,
ontology management, merchandizing, entity type detection, query
classification, word embeddings, query parsers, highlighting, analyzers,
tokenization, streaming expressions, faceting, concept clustering,
more like this, insight engine, apache lucene/solr, lucidworks fusion,
some kind of crazy magic, that white box with the magnifying glass...
What Is Search?

There are a LOT of skillsets required to
deliver a world-class Search experience

Ease of operations, scaling, and
performance are a top priority

We're drastically improving ease of operations

Time factors
•
And making the cluster aware of its own needs
Size factors Budget factors
• Scaling Policies
• Server Metrics
• Event Triggers
• Disk Space Free
• Prioritizing Traffic
• CPU Too High
• Traffic Increasing
• Need more Nodes
• Shards out of balance
• Back Pressure
• Traffic Increasing
• Server Lost

or.
How I indexed *.
... and lived to tell the tale ....
* simulated.
1.000.000.000.000
documents.

There is an ongoing shift away from "big data"
and toward actionable intelligence

Assistive Search is the new paradigm
•Requires personalization
•Voice
•Image Search
•Conversational
•Contextual (location, last search)
•Beyond links and information to  
Answers and Action

... and Search is now the de-facto user interface for  
digital interaction with your customers

The future of business success hinges on the
outcomes of billions of digital moments
FIND  
the correct
product
CONNECT  
to the right
person KNOW
exactly what
to do next
DRIVE
relevant
conversations
RESOLVE
a problem

Thank you!
@treygrainger
#Activate18 #ActivateSearch

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

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Artificial Intelligence Chap.5 : Uncertainty

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The Future of Search and AI

1. The Future of Search & AI Trey Grainger SVP of Engineering, Lucidworks @treygrainger #Activate18 #ActivateSearch

2. 612ATTENDEES 39COUNTRIES 70SESSIONS

4. So what are the current and   upcoming trends in Search & AI?

7. Big Data?

10.

11.

12.

13. We need big answers. Because we don’t need “big data.”

14.

15.

16.

17.

18. Solr leads the way on Learning to Rank

19.

20. And that mass adoption of LTR looks like this..

21. But what about all the other aspects of Search beyond AI?

22. relevance, scale, bm25, user experience, learning to rank, autoscaling, sys admin, server provisioning, lemmatization/stemming, cloud, docker, aws, natural language processing, etl, entity extraction, tf-idf, phrase detection, semantic search, query pipelines, connectors, web crawling, signals, real-time recommendations, personalization, question answering, request handlers, search components, autocomplete, spell checking, synonyms, stop words, query-log mining, probabilistic query parsing, boolean queries, geo-spatial queries, image search, voice search, classification models, bi- directional cross-datacenter replication, semantic knowledge graphs, ontology management, merchandizing, entity type detection, query classification, word embeddings, query parsers, highlighting, analyzers, tokenization, streaming expressions, faceting, concept clustering, more like this, insight engine, apache lucene/solr, lucidworks fusion, some kind of crazy magic, that white box with the magnifying glass... What Is Search?

23. There are a LOT of skillsets required to deliver a world-class Search experience

24. Scaling search can be really hard

25. Ease of operations, scaling, and performance are a top priority

26. We're drastically improving ease of operations

27. Time factors • And making the cluster aware of its own needs Size factors Budget factors • Scaling Policies • Server Metrics • Event Triggers • Disk Space Free • Prioritizing Traffic • CPU Too High • Traffic Increasing • Need more Nodes • Shards out of balance • Back Pressure • Traffic Increasing • Server Lost

28. or. How I indexed *. ... and lived to tell the tale .... * simulated. 1.000.000.000.000 documents.

29. Final Thoughts

30. There is an ongoing shift away from "big data" and toward actionable intelligence

31. Assistive Search is the new paradigm •Requires personalization •Voice •Image Search •Conversational •Contextual (location, last search) •Beyond links and information to   Answers and Action

32. ... and Search is now the de-facto user interface for   digital interaction with your customers

33. The future of business success hinges on the outcomes of billions of digital moments FIND   the correct product CONNECT   to the right person KNOW exactly what to do next DRIVE relevant conversations RESOLVE a problem

34. The Future of Search & AI Starts Now.

35. Thank you! @treygrainger #Activate18 #ActivateSearch

The Future of Search and AI

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