Proposal guidelines
Format:
Anthill Inside 2019 is a single track conference. Birds of Feather (BOF) sessions, round table discussions and office hours with speakers will be held in parallel with talks in the main auditorium.
We are accepting proposals for:
- Full-length (40 min) and crisp (20 min) talks.
- Birds of Feather (BOF) sessions – of 1 hour duration – on focussed topics.
- Tutorials, explaining core concepts in DL, ML and AI. Tutorials are of 1.5 hours to 2 hours duration.
- Hands-on workshops on Machine Learning, statistics, modelling, deep learning, NLP and Computer Vision.
Audience at Anthill Inside:
- Data scientists
- Senior AI engineers
- Architects
- Product managers
- Product engineers
- Founders and key decision makers from startups, mid-sized organizations and enterprises who are solving problems/facing challenges around running/managing infrastructure for AI and ML.
- Providers of managed services such as AWS, Google Cloud and Azure.
- GPU and CPU solution providers such as NVidia, Intel and others.
Topics for submitting talks, workshops, tutorials and BOF sessions:
-
Practical application of concepts, including:
1.1 Bayesian Networks
1.2 Reinforcement learning
1.3 Knowledge Graphs
1.4 Interpretability -
Data storage case studies: we are specifically interested in hearing about:
2.1 What do you do with data that has lost its currency?
2.2. How do you deal with privacy issues for vast amounts of irrelevant data? -
Tools for AI, ML and Deep Learning. Here, we want to hear about:
3.1 Whether you use third-party tools? If yes, why?
3.2 Do you adopt and retrofit existing tools? Again, why? Give us a detailed case study.
3.3 Do you develop tools for AI/ML/DL in-house? Why are in-house tools necessary for your case? -
Storing data on the cloud and cloud strategy.
4.1 Do you have a multi-cloud strategy? Share this with the community.
4.2 How do you deal with lock-in situations with single providers? -
GPU versus CPU – when you do use either and why? How do the strengths and limitations of each play out for your use case?
-
Case studies of practical applications of Computer Vision, NLP and Deep Learning to solve business problems.
Anthill Inside’s speaking policies:
We only accept one speaker per talk. This is non-negotiable. Workshops or tutorials may have more than one instructor.
Selection criteria:
The first filter for a proposal is whether the technology or solution you are referring to is open source or not. The following criteria apply for closed source talks:
- If the technology or solution is proprietary, and you want to speak about your propritary solution to make a pitch to the audience, you should pick up sponsored session. This involves paying for the speaking slot. Write to anthillinside.editorial@hasgeek.com for details.
- If your solution is closed source, you should consider proposing a talk explaining why you built it in the first place; what options did you consider (business-wise and technology-wise) before making the decision to develop the solution; or, what is your specific use case that left you without existing options and necessitated creating the in-house solution.
The criteria for selecting proposals, in the order of importance, are:
- Key insight or takeaway: what can you share with participants that will help them in their work?
- Structure of the talk and flow of content: a detailed outline – either as mindmap or draft slides or textual decription – will help us understand the focus of the talk, and the clarity of your thought process.
- Ability to communicate succinctly, and how you engage with the audience. You must submit link to a two-minute preview video explaining what your talk is about, and what is the key takeaway for the audience.
How to submit a proposal (and increase your chances of getting selected):
The following guidelines will help you in submitting a proposal:
- Focus on why, not how. Explain to participants why you made a business or engineering decision, or why you chose a particular approach to solving your problem.
- The journey is more important than the solution you may want to explain. We are interested in the journey, not the outcome alone.
- Show what participants from other domains can learn/abstract from your journey/solution.
- We do not accept how-to talks unless they demonstrate latest technology. If you are demonstrating new tech, show enough to motivate participants to explore the technology later.
- Similarly, we don’t accept talks on topics that have already been covered in the previous editions.
Passes and honorarium for speakers:
We pay an honararium of Rs. 3,000 to each speaker. Confirmed speakers also get a pass to the conference. We do not provide free passes for speakers’ colleagues and spouses. Please don’t ask us for this.
Travel grants for outstation speakers:
Travel grants are available for international and domestic speakers. We evaluate each case on its merits, giving preference to women, people of non-binary gender, and Africans. If you require a grant, request it when you submit your proposal in the field where you add your location. Anthill Inside is funded through ticket purchases and sponsorships; travel grant budgets vary.
Contact details:
For information about speaking or teaching workshops at Anthill Inside, write to anthillinside.editorial@hasgeek.com or call +91 7676332020
Submissions are closed for this project
All submissions
Production Object Detection - A Journey of Training, Building and Deploying CV modelsTarang Shah (@tarang27)
Technical level: Beginner
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Virtual Assistant for High Volume RecruitmentPiyush Makhija (@piyushmakhija)
Technical level: Intermediate
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Essential Python Recipes for Deep LearningAakash N S (@aakashns)
Section: Crisp talk
Technical level: Beginner
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Exploring the un-conventional: End-to-End learning architectures for automatic speech recognitionVikram Vij (@vikramvij)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Bandit algorithms to Reduce Cognitive Load on Customer Care Agents (Paper accepted for the demo track at SIGIR-2019)Hrishi Ganu (@blah)
Session type: Full talk of 40 mins
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Industrialized Capsule Networks for Text AnalyticsVijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran)
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Unsupervised Catalog Generation with Clustering, Reinforcement and MoreGovind Chandrasekhar (@gc20)
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Hacking Self-attention architectures to address Unsupervised text tasksVenkata Dikshit Pappu (@vdpappu)
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A Guide on Dynamic Parameter Estimation for Causal ForecastingTanmoy Bhowmik (@tanmoyb)
Session type: Lecture
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Building a Context-Aware Knowledge graph using Graph analysis & Language modelsShashank Rao (@shashankpr)
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Use cases of Financial Data Science Techniques in retailSudipto Pal (@sudipto-pal)
Section: Crisp talk
Technical level: Intermediate
Session type: Lecture
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Yes! Attention is all you need for NLPsimrat (@sims)
Session type: Lecture
Session type: Full talk of 40 mins
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Weaponising Artificial Intelligence In Cyber Security - The Next Age of Cyber Security EndgameVanshit Malhotra (@vanshit)
Section: Crisp talk
Technical level: Intermediate
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Email Data AnalyticsRahul Sharma (@rahulks)
Session type: Lecture
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AgentBuddy: Leveraging Bandit Algorithms for a human-in-loop system for Customer Care Agents (Paper accepted for the demo track at SIGIR-2019)Mithun Ghosh (@mithunghosh)
Section: Full talk
Technical level: Intermediate
Session type: Demo
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Productionizing deep learning workflow with Hangar, <frameworkOfYourChoice> & RedisAISherin Thomas (@hhsecond)
Technical level: Intermediate
Section: Workshops
Session type: Workshop
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Non-Intent User Similarity for recommendation systemsGunjan Sharma (@gunjan-sharma)
Section: Full talk
Technical level: Intermediate
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Annotate This! A simple tool that seeks to simplify the creation of annotated text datasets - primarily for Hindi and other vernacular Languageskarmanya aggarwal (@calmdownkarm)
Section: Crisp talk
Technical level: Beginner
Session type: Demo
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Tensorboard: Almost a one stop shop for Machine Learning DevelopmentTushar Pawar (@tuuushaar)
Section: Full talk
Technical level: Beginner
Session type: Lecture
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Hands on Deep Learning for Computer Vision – Techniques for Image Segmentation.(6 hours workshop).usha rengaraju (@usharengaraju)
Section: Workshops
Technical level: Intermediate
Session type: Workshop
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Introduction to Bayesian Networks(3 hour workshop)usha rengaraju (@usharengaraju)
Section: Workshops
Technical level: Beginner
Session type: Workshop
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Reinforcement LearningSuraj Sheth (@shethsh)
Section: Workshops
Technical level: Intermediate
Session type: Workshop
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Out of Distribution Detection in Deep Learning ClassifiersAkhil Lohia (@alohia)
Section: Crisp talk
Technical level: Intermediate
Session type: Lecture
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Explainable AI: Behind the ScenesManjunath (@manjunath-123)
Section: Tutorials
Technical level: Intermediate
Session type: Tutorial
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Feature selection and engineering using genetic algorithms and genetic programmingSIDHARTH KUMAR (@sidkumar)
Section: Full talk
Technical level: Advanced
Session type: Lecture
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Interpret-ability as a bridge from Insights to Intuition in Machine and Deep LearningSai Sundarakrishna (@psgsai)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Tools for AI & ML for machine learning at Scale.Saurabh Misra (@saurabh-appd)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Using Locations for Online-Behaviour Prediction with Sparse DataNishant Oli (@nishantoli)
Section: Crisp talk
Technical level: Intermediate
Session type: Lecture
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Snorkeling in the deep: Bootstrapping an NLU modelShubhangi Agrawal (@shubhangia)
Section: Crisp talk
Technical level: Beginner
Session type: Lecture
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Using AI for improving performance and design of ad creativesFarhat Habib (@distantfedora)
Technical level: Intermediate
Session type: Lecture
Section: Crisp talk
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Bridging the gap between research to the deployment of Machine Learning modelsNilesh Patil (@nilesh-patil)
Section: Full talk
Technical level: Intermediate
Session type: Workshop
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Modeling the effects of blurriness in mobile adsAbhijith C (@abhijith-c)
Section: Crisp talk
Technical level: Intermediate
Session type: Lecture
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Large scale Machine Learning and data storage for CDP: transforming Digital MarketingKunal Kishore (@kunalkishore)
Technical level: Intermediate
Session type: Lecture
Section: Full talk
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End to End Computer Vision paradigm with respect to advanced deep learning techniques.Pushkar Pushp (@ppushp7)
Technical level: Intermediate
Section: Tutorials
Session type: Tutorial
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GAN-inspired Innovations in Computer VisionPushkar Pushp (@ppushp7)
Technical level: Intermediate
Session type: Lecture
Section: Tutorials
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Practical Recommendation Systems: Scalability, Accuracy, LatencyKunal Kishore (@kunalkishore)
Section: Tutorials
Technical level: Intermediate
Session type: Tutorial
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Opening the Black Box: How to Interpret Machine Learning models; techniques, tools, and takeawaysFarhat Habib (@distantfedora)
Section: Workshops
Technical level: Intermediate
Session type: Workshop
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Advanced NLP and Deep Learning for document classification - A case study in civil aviation safety prognosisprabhakar srinivasan (@prabhacar7)
Section: Tutorials
Technical level: Intermediate
Session type: Tutorial
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Taking AI Products to MarketPuneeth N (@puneethnarayana)
Section: Birds Of Feather (BOF) session
Technical level: Intermediate
Session type: Lecture
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Attention based sequence to sequence models for natural language processingMadhu Gopinathan (@mg123)
Section: Workshops
Technical level: Intermediate
Session type: Workshop
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Learning to Rank framework for product recommendation - Ranknet to LambdaMART to Groupwise scoring functions - experimentsnarasimha m (@6544)
Session type: Full talk of 40 mins
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Dataset Denoising : Improving Accuracy of NLP ClassifierKhaleeque Ansari (@khaleeque-ansari)
Section: Crisp talk
Technical level: Intermediate
Session type: Lecture
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Learning to Rank recommendation - Ranknet to LambdaMART to Groupwise scoring functions - experiments, introduction to Tensorflow Rankingnarasimha m (@6544)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Network health predictions and optimization recommendation using Deep learning Neural network models and Reinforcement learningAnuradha K (@anuradhak)
Section: Workshops
Technical level: Intermediate
Session type: Workshop
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NLP bootcampAnuj Gupta (@anuj-gupta)
Session type: Workshop
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Recommendation @ ScaleAditya Patel (@adityap)
Section: Crisp talk
Technical level: Intermediate
Session type: Lecture
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Portfolio Optimization using Deep Reinforcement LearningSonam Srivastava (@sonaam1234)
Section: Full talk
Technical level: Advanced
Session type: Demo
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Accountable Behavioural Change Detection (VEDAR) using Machine LearningSrinivasa Rao Aravilli (@aravilli)
Session type: Short talk of 20 mins
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Time Series Anomaly detection on structured data from IOT Network using CNNprasenjeet acharjee (@pac1310)
Session type: Short talk of 20 mins
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Introduction to Probabilistic Programming - PyMC3 and EdwardHariharan C (@harc)
Section: Tutorials
Technical level: Intermediate
Session type: Tutorial
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Generation of Newsletter using Natural Language GenerationRajesh Gudikoti (@ragudiko)
Section: Crisp talk
Technical level: Beginner
Session type: Lecture
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iCASSTLE: Imbalanced Classification Algorithm for Semi Supervised Text LearningDebanjana Banerjee (@debanjana)
Session type: Short talk of 20 mins
Section: Full talk
Technical level: Advanced
Session type: Lecture
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Design a real-time anomaly detection application using Spark and Machine LearningANKIT JAIN (@ankitjain22)
Section: Crisp talk
Technical level: Beginner
Session type: Discussion
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Building a time series model using CNNs and GANsprasenjeet acharjee (@pac1310)
Session type: Short talk of 20 mins
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Machine Learning Model and Dataset VersioningKurian Benoy (@kurianbenoy)
Section: Crisp talk
Technical level: Intermediate
Session type: Lecture
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Using NLP to generate QuizzesVishal Gupta (@vizgupta)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Birds of a Feather on InterpretabilityJacob Joseph (@jacjose) via Abhishek Balaji (@booleanbalaji)
Section: Birds Of Feather (BOF) session
Technical level: Intermediate
Session type: Discussion
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Myths and Realities of Data Labeling for Deep LearningVijay Gabale
Section: Birds Of Feather (BOF) session
Technical level: Intermediate
Session type: Discussion
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Demystifying deep reinforcement learningUma Sawant (@umasawant)
Section: Workshops
Technical level: Intermediate
Session type: Workshop
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PySpark for GeoSpatial DataPrakhar Srivastava
Section: Tutorials
Technical level: Beginner
Session type: Tutorial
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Building Products with ML: A Workshop for Product & Engg Managerslavanya TS (@lavanyats)
Section: Workshops
Technical level: Intermediate
Session type: Workshop
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Feast: Feature Store for Machine LearningWillem Pienaar
Section: Full talk
Technical level: Beginner
Session type: Lecture
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Document digitization - Rethinking it with Deep LearningNischal HP (@nischalhp)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Tutorial on Testing of Machine Learning ApplicationsSandya Mannarswamy (@sandyasm)
Section: Tutorials
Technical level: Intermediate
Session type: Tutorial
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Rigorous Evaluation of NLP Models for Real World DeploymentSandya Mannarswamy (@sandyasm)
Section: Full talk
Technical level: Intermediate
Session type: Discussion
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Hangar; git for your dataSherin Thomas (@hhsecond)
Section: Full talk
Technical level: Intermediate
Session type: Demo
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Probabilistic Modeling – a tutorial on Bayesian NetworksAshish Kulkarni (@kulashish)
Section: Tutorials
Technical level: Intermediate
Session type: Tutorial
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Building a Recommendation Engine for diverse content and user behaviorsPriyanshu Chandra (@priyanshu-chandra)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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How we built our own scalable, real-time framework to create and serve conversational systems.Ved Mathai (@vedmathai)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Artificial Intelligence for automated investmentmira abboud (@mira-abboud) via Zainab Bawa (@zainabbawa)
Section: Full talk
Technical level: Advanced
Session type: Lecture
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Sizing biological cells and saving lives using AISrikanth Gopalakrishnan (@srikrvd91)
Section: Birds Of Feather (BOF) session
Technical level: Intermediate
Session type: Demo
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Model Interpretability, Explainable AI and the Right to InformationDivij Joshi
Section: Crisp talk
Technical level: Beginner
Session type: Discussion
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Blueprint for Building AI ProductsAmit Baldwa (@abaldwa)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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What can software learn from robots and mathNaman Kumar (@namankumar) via Zainab Bawa (@zainabbawa)
Section: Full talk
Technical level: Advanced
Session type: Lecture
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The shape of UNishant Sinha (@ekshaks) via Zainab Bawa (@zainabbawa)
Section: Crisp talk
Technical level: Advanced
Session type: Lecture
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ML application lifecycle: recommendations for each stageSrujana Merugu (@srujana-merugu) via Zainab Bawa (@zainabbawa)
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Efficient Machine Translation for low resource languages using TransformersNickil Maveli (@nickil21)
Session type: Full talk of 40 mins
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Build an enterprise grade data labelling pipeline to scale your ML/AI pipelinesBikram Sengupta (@bikramsengupta)
Session type: Full talk of 40 mins
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How we applied sampling algorithms to extract meaning from data (@ Belong.co)Vinodh Kumar Ravindranath (@vinodh-kumar)
Session type: Full talk of 40 mins
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Gendered Biases in Artificial IntelligenceRadhika Radhakrishnan (@radhika-radhakrishnan)
Session type: Full talk of 40 mins
Section: Full talk
Technical level: Intermediate
Session type: Lecture
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Open Source Tools and Archive for Tackling Misinformation on ChatApps in IndiaKeshav Joshi (@kmjoshi) via Tarunima Prabhakar (@flicker91)
Session type: Short talk of 20 mins
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