Anthill Inside 2017
On theory and concepts in Machine Learning, Deep Learning and Artificial Intelligence. Formerly Deep Learning Conf.
Jul 2017
24 Mon
25 Tue
26 Wed
27 Thu
28 Fri
29 Sat 09:00 AM – 05:40 PM IST
30 Sun
##About AnthillInside:
In 2016, The Fifth Elephant branched into a separate conference on Deep Learning. Anthill Inside is the new avataar of the Deep Learning conference.
Anthill Inside attempts to bridge the gap bringing theoretical advances closer to functioning reality.
Proposals are invited for full length talks, crisp talks and poster/demo sessions in the area of ML+DL. The talks need to focus on the techniques used, and may be presented independent of the domain wherein they are applied.
We also invite talks on novel applications of ML+DL, and methods of realising the same in hardware/software.
Case studies of how DL and ML have been applied in different domains will continue to be discussed at The Fifth Elephant.
https://anthillinside.in/2017/
##Format:
Anthill Inside is a two-track conference:
We are inviting proposals for:
You must submit the following details along with your proposal, or within 10 days of submission:
##Selection Process:
We expect you to submit an outline of your proposed talk, either in the form of a mind map or a text document or draft slides within two weeks of submitting your proposal to start evaluating your proposal.
You can check back on this page for the status of your proposal. We will notify you if we either move your proposal to the next round or if we reject it. Selected speakers must participate in one or two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.
A speaker is NOT confirmed a slot unless we explicitly mention so in an email or over any other medium of communication.
There is only one speaker per session. Entry is free for selected speakers.
We might contact you to ask if you’d like to repost your content on the official conference blog.
##Travel Grants:
Partial or full grants, covering travel and accomodation are made available to speakers delivering full sessions (40 minutes) and workshops. Grants are limited, and are given in the order of preference to students, women, persons of non-binary genders, and speakers from Asia and Africa.
##Commitment to Open Source:
We believe in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like for it to be available under a permissive open source licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), you should consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support the conference in return for giving you an audience. Your session will be marked on the schedule as a “sponsored session”.
##Important Dates:
##Contact:
For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.
Please note, we will not evaluate proposals that do not have a slide deck and a video in them.
Hosted by
Vijay Gabale
Basis for the discussion:
Technology is getting commoditized rapidly. Google, FB are on open source spree that solves hard problems. However, there is still scope to build vertical specific AI products.
The goal is to seek answers to the below questions:
Part 1: busting the AI myth
Critique questions:
Do you really apply deep learning (or AI)
What is the size of dataset that you play with
What is more painful: collecting data or applying AI
How do you map effect/outcome of deep learning (or AI) on product metrics
Part 2: dark data
The data advantage
The user advantage
Building a product that has a loop between users and data
Is data your core advantage (and not technology)
How fast can your competitors have the same data (or technology)
Part 3: building products
B2B (or SAAS) product vs consulting
Since you don’t own data, how do you build a scalable product
If there is too much customization required to serve every customer, how do you build a business
B2C product vs technology
How do you build defensibility with AI
Do you build good to have features for existing market or a scalable product to serve new market
Patents vs 10X improvement in technology via research
Part 4: product-customer experiences
Has AI delivered on its promise so far
What more needs to be done
Panelists:
Anuj Gupta is a senior ML researcher at Freshdesk; working in the area NLP, Machine Learning, Deep learning.
Jaisimha Rao is the CEO of TartanSense that uses drone sensing and aerial image processing to aid agriculture.
Saad Nasser is the co-founder of AtiMotors. He handles technology at Ati where he works across autonomy, power electronics, and vehicle design.
Alpan Raval is the manager of the content quality relevance team at LinkedIn.
Facilitator:
Vijay Gabale is co-founder and CTO of Huew, an AI-powered Commerce Platform.
Hosted by
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