The top 14 AI and machine learning conferences to attend in 2018
Artificial intelligence and machine learning have leapt off the pages of science fiction novels and burst into the real world. These technologies have game-changing implications for businesses of all sizes, whether you’re planning to implement them yourself or contemplate the consequences of their adoption on the world at large. With these fields moving so fast, it's hard to stay on top of big changes, let alone smaller advances that can affect IT organizations and you personally.
That's where AI and machine learning conferences come in. There's no better way to advance your career, learn new AI and ML skills, make new human connections, and maybe some non-human ones as well. And because these fields are hotter than a gaming laptop with a busted fan, this the perfect time to ask your boss to invest in helping you learn more about both.
However, not every conference is a good use of your corporate travel budget. To help you make the most of your time and money, we created a list of recommended AI and machine learning conferences scheduled for 2018.
Each listing includes dates, locations, social media connections, agenda highlights, and pricing. The event websites provide more details, but this summary helps you create a travel short list of your own.
It’s early, though. In many cases, conference organizers haven’t announced their full schedules, with information “to be determined.” However, this overview should enable you to start planning your year.
The list is sorted by date, although some conferences are held multiple times a year in different locations, so there may be an event convenient to you.
Must-attend AI and machine learning conferences
If you have the time and budget to attend only one conference in 2018, choose one from this section. These events are well established and run by respected organizations. They pack a lot of depth into the agenda: speakers, training, workshops, sessions, and lots of chances to meet and mingle.
Global Artificial Intelligence Conference
- Twitter: #GAIC
- Web: http://www.globalbigdataconference.com/santa-clara/global-artificial-intelligence-conference/event-97.html
- Date: January 17-19, 2018
- Location: Santa Clara, CA
- Cost: $699 to $1,499, depending on the number of days you attend.
With a broad program spanning AI topics in several industry verticals, the Global Artificial Intelligence Conference is a jam-packed three-day event.
The tracks include technology (e.g., cognitive computing, chatbots, NLP, computer vision, and neural networks) and industry topics (e.g., telecom, finance, and travel/transportation). A sample of the presentations include, "IOT And Machine Learning: Transforming the Security Space," "Business Transformations thorough IoT and AI," and "Predicting Alzheimer’s Disease With Machine Learning."
In addition, workshop tracks let you dive in deep, with topics like "Enhancing NLP with Deep Neural Networks," "Frameworks Galore: Which One to Pick," and "Keras."
Who should attend: Business executives responsible for AI initiatives, heads of innovation, heads of product development, analysts, project managers, analytics managers, data scientist, statisticians, AI and software developers, AI consultants and service providers, students, and data analysts.
REWORK Deep Learning Summit
- Twitter: @reworkdl / #reworkdl
- Dates and Locations: January 25-26, 2018 (San Francisco), May 24-25, 2018 (Boston), September 20-21, 2018 (London), October 25-26, 2018 (Toronto: Track 1 and Toronto: Track 2)
- Cost: $1,495 to $2,095. Discounts for early birds, students, full-time academics, and startups.
REWORK's Deep Learning Summits are two-day conferences held throughout 2018. Each event promises to share advances in deep learning algorithms and methods, highlight emerging trends, and connect industry innovators, technologists, data scientists, and startup founders in the deep learning world.
The conference schedule includes speakers from Google, Netflix, Adobe, and Ancestry.com, with presentation topics including "Deep Learning in Production at Facebook," "Computer Vision Algorithms for Camera Calibration and Object Tracking," "Deep Learning for Recommender Systems," and "End-to-End Deep Learning for Detection, Prevention, and Classification of Cyber Attacks."
Longer workshops go into depth on topics such as "System Infrastructures for AI and ML Software," "Creating an AI Strategy for Your Workplace," and "An Introduction to AI for Enterprise."
One attendee found the Deep Learning Summit to be "an interesting mix of both industry and academic. REWORK did more than enough to prove their professionalism and attention to detail, and this is without mentioning the calibre of speakers they secured for the event."
Who should attend: Data scientists, data engineers, machine learning scientists, CTOs, founders, director of engineering, CEOs.
O’Reilly Artificial Intelligence Conference
- Twitter: @TheAIConf / #TheAIConf
- Web: https://conferences.oreilly.com/artificial-intelligence
- Dates and locations: April 10-13, 2018 (Beijing), April 29 – May 2, 2018 (New York), September 4-7, 2018 (San Francisco), October 8-11, 2018 (London)
- Cost: Early pricing for San Francisco is $1,445 (Bronze), $1,845 (Silver), and $2,245 (Gold). Pricing for London isn't available yet.
O'Reilly's Artificial Intelligence Conferences are a series of standalone events in different locations throughout the year. Their overarching theme is "Put AI to work," and with both technical and non-technical presentations, the conferences focus on bridging the gap between theory and practical applications. Keynote speakers hail from academic institutions such as MIT and Carnegie Mellon University and include business leaders from companies like Google and Salesforce.
For example, at a 2017 conference, Andrew Ng, co-founder and co-chairman of Coursera, advised engineers to read academic papers and implement those approaches to replicate the results. "That will not only lead to a deeper understanding of the advanced concepts," he insisted, "but also help you in coming up with new ideas."
Each conference kicks off with two-day training sessions including "Natural language processing with deep learning" and "Deep learning with TensorFlow." The preview day has tutorials on topics such as "Here and now: Bringing AI into the enterprise," "Deep reinforcement learning tutorial," and “Introduction to neural networks with Keras."
The two main conference days are organized by track. For example, the 2017 New York schedule was divided into the following topics:
- Impact of AI on business and society: "Will we automate jobs faster than we create them?" "Planning for the social impact of AI," and "AI's legal history and some notions of the future."
- Implementing AI: "Strategies for integrating people and machine learning in online systems," "Tackling the limits of deep learning," and "Deep learning applied to consumer transactions with Think Big Analytics."
- Interacting with AI: "Conversational AI at large scale," "Bigger than bots: Machine reading and writing in enterprise," and "Deep shopping bots: Building machines that think and sell like humans."
- Verticals and applications: "AI for manufacturing: Today and tomorrow," "Cognitive mobile healthcare for the patient and physician," and "Transforming an investment firm with AI: A case study."
Diversity is strongly encouraged, and the extra effort seems to be making a difference: "Awesome how many female AI rockstars presented at #TheAIConf. AI is not taking over humans; women are taking over AI. ;-)"
Who should attend: Algorithm engineers/scientists, chief experience officers, data scientists/engineers, research scientists, software engineers, business analysts, those in charge of innovation initiatives, product marketing managers, product managers, and program managers.
Conference on Neural Information Processing Systems
- Twitter: @NipsConference / #NIPS / #NIPS2018
- Web: https://nips.cc/Conferences/2018
- Date: December 3-8, 2018
- Location: Montreal
- Cost: TBD
AI is not a new field. The 2018 Conference on Neural Information Processing Systems (NIPS) is the 32nd event. Nearly 8,000 people attended the 2017 conference in Long Beach, California. What makes it special? The 2017 agenda should help you decide if this is the right event for you:
- Invited talks: "Why AI Will Make It Possible to Reprogram the Human Genome," "The Trouble with Bias," and "Deep Learning for Robotics."
- Oral presentations of academic papers: "A graph-theoretic approach to multitasking," "Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System," and "Quantifying How Much Sensory Information in a Neural Code Is Relevant for Behavior."
- Demos: "A Deep Reinforcement Learning Chatbot," "Babble Labble: Learning from Natural Language Explanations," and "Sensomind: Democratizing Deep Learning for the Food Industry."
- Workshops: "Visually grounded interaction and language," "Machine Learning for Audio Signal Processing (ML4Audio)," and "Conversational AI: Today's Practice and Tomorrow's Potential."
And there's a competition track where bots square off against each other for a prize.
If you’re looking for a job change, NIPS is the place to be. NIPS 2017 was called "a recruiting frenzy more akin to the National Football League’s draft day." Go get 'em, tiger.
If you’re interested, don’t dawdle; each year, the event sells out.
Who should attend: As the agenda suggests, this is techie stuff suitable for researchers, data scientists, and engineers.
The Machine Learning Conference
- Twitter: @mlfconf / #MLconfSF / #MLconfATL / #MLconfSEA / @MLconfNYC
- Web: https://mlconf.com
- Dates and locations: TBD (New York), TBD (Seattle), TBD (Atlanta), November 14, 2018 (San Francisco)
- Cost: San Francisco starts at $150.
The Machine Learning Conference is a series of multicity events in multiple cities. Each is a single-day event that aims to disseminate recent machine learning research and industry applications.
The event strives to be agnostic, and past programs suggest that it achieves this goal. From "Large-Scale Machine Learning: Deep, Distributed and Multi-Dimensional" to "Lessons Learnt from Building ML Products for Enterprise SaaS," and "Can Machine Learning Save the Whales?" it’s evident that there’s plenty of technical material for machine learning practitioners. The September 2017 San Francisco conference speakers included Ted Willke, an Intel senior principal engineer; Josh Wills, Slack’s head of data engineering; Franziska Bell, a data science manager on the platform team at Uber; and Rushin Shah, an engineering leader at Facebook.
This conference, too, gets a thumbs-up for diversity. Worried about the gender gap in data science? Rafael Carrascosa says that women gave the best two talks at MLconf San Francisco 2017.
Who should attend: Students and practitioners who want tips and methodologies to apply in their own work, as well as cited papers and code samples to reference for research.
The AI Conference
- Twitter: @AIconference
- Web: http://aiconference.com/events/2017-san-francisco
- Date: TBD
- Location: TBD
- Cost: TBD
The AI Conference is organized by the same folks who run the Machine Learning conference, with a different structure. This single-day event about emerging technologies in AI puts a focus on AI projects. In addition to deeply technical presentations on AI, related topics include law, ethics, safety, and governance.
Both presentations and speakers are top notch. At 2017's event in June, these included "Conversational AI in Amazon Alexa," presented by Ashwin Ram, senior manager of AI science for Alexa; "How Might Artificial Intelligence Come About? Different Approaches and Their Implications for Life in the Universe," presented by science fiction author David Brin (you probably know him best from "The Postman"); and "Emotional Trauma and Machine Learning," by Caroline Sinders, an online harassment researcher at Wikimedia.
Who should attend: Some AI conferences are extremely technical. Those looking for more general insights about the future of AI may want to consider this one.
These events focus on a thin slice of AI and machine learning, either a sub-discipline or industry vertical, and might not be for all. However, if their niche matches with yours, these conferences can be a valuable part of your 2018 plans.
REWORK AI Assistant Summit
- Twitter: @reworkAI / #reworkAI
- Dates and Locations: January 25-26, 2018 (San Francisco), March 15-16, 2018 (London)
- Cost: $1,495 to $2,095 (San Francisco); £795 to £1,495 (London). Discounts for early birds, students, full-time academics, and startups.
If you're into natural language processing, then the REWORK AI Assistant Summit is not to be missed. The event focuses on using machine and deep learning to create AI assistants as well as conversational interfaces.
Among the sessions are "NLP, Parsing, Information Extraction, Dialog and Question Answering," "Embodied Socially Assistive Agents: Going Beyond Assistance and Towards Behavior Change," and "The Role of Personality and Emotion in Spoken Interactions." Presenters hail from innovators at Apple, Autodesk, and x.ai.
Who should attend: Data scientists, data engineers, developers, entrepreneurs, CTOs, CEOs, investors.
International Conference on Learning Representations
- Twitter: @iclr2017
- Web: https://iclr.cc/
- Date: April 30 – May 3, 2018
- Location: Vancouver, BC, Canada
- Cost: Not available (last year’s registration was €900)
Among topics are feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization. If conference sessions with titles like “Amortised MAP Inference for Image Super-resolution” make you say, “Oh, cool!” this conference is likely worth your time.
Who should attend: This is a deeply technical conference that should appeal to practitioners working on moving the field forward in unsupervised, semi-supervised, and supervised representation learning; representation learning for planning and reinforcement learning; and metric learning and kernel learning.
REWORK Machine Intelligence Summit
- Twitter: @reworkMI / #reworkMI
- Web: https://www.re-work.co/events/machine-intelligence-summit-hong-kong-2018
- Date: June 6-7, 2018
- Location: Hong Kong
- Cost: HK$7,995 to HK$10,995, with early-bird pricing and discounts for students, full-time academics, and startups.
Will smart artificial intelligence finally rival human intelligence? The REWORK Machine Intelligence Summit explores trends in the development of intelligent machines to make sense of data and ML’s impact on business and society.
The draft agenda lists a wide range of topics, including "Optimising Convolutional Neural Networks for Embedded Platforms," "Computer Vision for Quality Control and Inspection," and "Predicting Human Behaviour Through Mobile Sensing." Speakers represent Tesla, HSBC, NASA Ames Research Center, and other innovators in the field.
Who should attend: Data scientists, data engineers, machine learning scientists, developers, entrepreneurs, directors of engineering, big data experts.
Conference on Computer Vision and Pattern Recognition
- Twitter: @CVPR / #CVPR2018
- Web: http://cvpr2018.thecvf.com
- Date: June 18-22, 2018
- Location: Salt Lake City
- Cost: Standard Passport pricing ranges from $675 to $1,000, with early-bird discounts. A standard one-day workshop/tutorial pass ranges from $325 to $425.
The eponymously focused Conference on Computer Vision and Pattern Recognition event is comprised of a main conference, during which papers and keynote speeches are presented, as well as workshops and short courses.
While the 2018 schedule has not yet been shared (and the call for papers has not been announced), the 2017 conference event had workshops, tutorials, and presentations of academic papers. The oral and spotlight sessions were about 3D vision, machine learning, low- and mid-level vision, analyzing humans in images, biomedical image/video analysis, and object recognition and scene understanding. Sample papers presented were "Emotion Recognition in Context," "Anti-Glare: Tightly Constrained Optimization for Eyeglass Reflection Removal," "Generalized Rank Pooling for Activity Recognition," and "Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs."
Tutorials included full- and half-day sessions on topics such as "DIY: A Multiview Camera System: Panoptic Studio Teardown," and "Mathematics of Deep Learning." Workshops included "Biometrics," "Women in Computer Vision," and "Traffic Surveillance Workshop and Challenge." Finally, there's a vendor exhibit hall as well as recruiting booths.
Who should attend: Students, academics, and industry researchers in the field of machine vision.
REWORK AI in Industrial Automation Summit
- Twitter: @reworkauto /#reworkAUTO
- Web: https://www.re-work.co/events/ai-industrial-automation-summit-san-francisco-2018
- Date: June 28-29, 2018
- Location: San Francisco
- Cost: $1,495 to $1,895. Early-bird pricing available, with discounts for students, full-time academics, and startups.
If you work in manufacturing, REWORK's AI in Industrial Automation Summit deserves a spot on your 2018 schedule. The event focuses on the impact of machine learning on industrial automation. The draft 2018 suggests presentations such as "Time Series Data & Data for Predictive Maintenance," "Using AI with Sensor and Signal Data," and "Deep Learning and Applications in Industrial Automation." Planned speakers come from Amazon, Procter & Gamble, Google, and other driving forces.
Who should attend: This is for techies, including lead software engineers, chief data scientists, CTOs, founders, directors of engineering, CEOs, and system engineers.
AI World Conference and Expo
- Twitter: @AIWorldExpo
- Web: https://aiworld.com
- Date: December 3-5, 2018
- Location: Boston
- Cost: 3-day pass is $2,195, 2-day pass is $1,795, 1-day pass is $1,295, and an expo pass is $299. Early-bird pricing is available.
It’s too early to say much about the 2018 AI World Expo, since the 2017 event just concluded. But a glance at the 2017 agenda makes it an intriguing conference to consider, with 150 speakers addressing data science techniques, use cases for AI and high-performance computing, and case studies such as banks' adoption of intelligent assistants and bots to handle customer service inquiries.
Who should attend: Business and technology executives responsible for AI initiatives.
Other conferences of note
This final section lists smaller or newer conferences that may be the best conferences you never heard of.
AAAI Conference on Artificial Intelligence
- Twitter: @RealAAAI / #AAAI2018
- Web: https://aaai.org/Conferences/AAAI-18
- Date: February 2-7, 2018
- Location: New Orleans
- Cost: $925, with early-bird pricing and discounts for AAAI members and students.
Put on by the Association for the Advancement of Artificial Intelligence, the AAAI Conference on Artificial Intelligence aims to promote AI research and a scientific exchange among attendees. This event is paper-focused presentations. Some of the papers accepted and presented in 2017 included "AI for Complex Situations: Beyond Uniform Problem Solving," "Enabling Autonomous Space Mission Operations with Artificial Intelligence," and "Fast and Personal: Scaling Deep Learning with MxNet."
The program also includes tutorials and workshops as well as student programs and a job fair.
Who should attend: AI researchers, practitioners, scientists, engineers, and academics.
Intelligent Systems Conference
- Twitter: #IntelliSys2018
- Web: http://saiconference.com/IntelliSys
- Date: September 6-7, 2018
- Location: London
- Cost: £500, with student discounts.
The Intelligent Systems Conference 2018 is an academic and research-based event with keynote speakers representing industry leaders. Last year's conference saw papers such as "Towards Stream-based Reasoning and Machine Learning for IoT Applications," "A Modified Penalty Function in Fuzzy Clustering Algorithm," and "Intelligent Search with Deep Learning Clusters."
Who should attend: Researchers and industry practitioners.
Did we miss any AI and machine learning conferences? Tweet us about additions at @enterprisenxt.
This article/content was written by the individual writer identified and does not necessarily reflect the view of Hewlett Packard Enterprise Company.