Bengaluru Tech Summit : Day 1
Damiel Manuel talked about Cyber Security. In this world, millions and billions of people are active on various social media like Facebook, WhatsApp, Instagram, YouTube, LinkedIn etc. It rises "deep fake" video threat. The video footage that appears to be real but is produced by technology. Now, we can no longer believe our eyes. NIST is a cyber security framework. Link 1 and Link 2 Cyber security is also a layered architecture. Hardware and network security is at physical layer. Application/software security at logical layer. Data security includes protection of personal information, location, accessibility, integrity of data etc. Social aspects covers people, culture and processes. it needs more attention. Cyber security topic now moves to Cyber resilience
Interesting panel discussions about AI/ML.
Ajay Sharma : Machine used to crunch numbers and humans make decision. Now machines are capable of doing both. Use cases (1) use Intel Mobileye to prevent, predict accident zones. (2) CheXNeXt is deep learning for chest radiograph diagnosis. Discussion about Niti Ayog #AIforAll ICTAI (International Center for Transformative AI) etc.
Raj Cherubal: Smart City solutions : (1) Parking management system (2) public bicycle sharing (3) restoration of water bodies (ponds) (4) solar panel on government buildings (5) water meter (6) smart class (7) disaster management system etc. IUDX (Indian Urben Data Exchange) Link Whitepaper Link
Aksah Ravi (gnani) talked about NLP based voice assistant products that supports Hindi, Kannada etc.
Out of all AI/ML projects hardly 13 to 14 % projects are successful and only 8% of customer are happy. Some projects need their ML model to be updated every week, even every day. AI/ML business case is all about identifying and satisfying unmet and unmentioned need. Few challenges (1) AI/ML implementation needs cultural change, where man and machine both work together. (2) upskill of existing staff (3) Data is fuel for AI. More time goes to find out which data to use rather than building AI/ML model. Noise in data can cause bias. The chatbot may learn offensive language over time. (4) explain-ability of AI/ML outcome. (5) Robust governance is also important. At present, chatbots are becoming popular. Long way to go. Information architecture (IA) is must for AI/ML projects. IA is the structural design of shared information environments.
Queryplex and federation are effective tools from IBM to connect multiple data sources. AI OpenScale is another tool from IBM
Ashok Ayengar talked about shopx - buy and sale platform.
Last 25 years of history big enterprise adopted new technologies like ERP and small stratup companies built eco-system around it. Many fortune 500 companies have huge legacy in range of 20 to 100 years. They need machine learning even on end-of-life servers.
The collaboration at Bangalore is not seen even in developed country. Here we have hackathon, open source contribution, discussion at physical meetup etc. It is really proud to be in Bangalore.
The day 1 ended with thought leaders conclave on "TechScape 2035"
The following trends are emerged.
1. Digitalization
2. Rapid Urbanization
3. Customer does not want product, but wants solution
4. so more and more collaborations
The growth of Internet was not predicated.
1. Growth with many IoT devices
2. Growth for amusement e.g. Netflix
3. Many networks E.g. Car has many networks
During 90s, when Internet based innovative services and business was planned, no one predicated that everyone (4 billion people) will have smart phone. Now cost of computing come down. Technology is democratized. This growth will be accelerated further, as everything (e.g. speaker, light etc.) will have compute power, connectivity, intelligent (AI/ML). The enormous data is generated by our wearable. Evolution will happen in laboratory and new human being will be created. Excitement with fear.
Now the smart software makes diagnosis smarter than doctor. In next 5 to 10 years, it will be mandatory to take second opinion from machines. People will get incentive for not being sick by health insurance and hospitals. The Indian doctors and nurses are best in the world. This is a license driven industry.
Now in automobile people need : 0 emission, 0 downtime, 0 accident, and first solution is electric car. Electricity is alternate fuel. The omnipresent 3D printing will eliminate need to keep inventory of spare parts of cars. The digitization, GST have improved logistics a lot. We need more efficiency steps like: spare trailers will just replace the loaded one to save time.
All these trends will empower the bottom of pyramid, surprisingly.
In future, there is no concept of firm. All companies are becoming platform. Apple started as platform for iOS apps. People starts company just on WhatsApp group. Now we will see rapid consolidation of firms. So monopoly will be back.
The present generation is Digital Native and generation Z Their working style is completely different.
Interesting panel discussions about AI/ML.
Ajay Sharma : Machine used to crunch numbers and humans make decision. Now machines are capable of doing both. Use cases (1) use Intel Mobileye to prevent, predict accident zones. (2) CheXNeXt is deep learning for chest radiograph diagnosis. Discussion about Niti Ayog #AIforAll ICTAI (International Center for Transformative AI) etc.
Raj Cherubal: Smart City solutions : (1) Parking management system (2) public bicycle sharing (3) restoration of water bodies (ponds) (4) solar panel on government buildings (5) water meter (6) smart class (7) disaster management system etc. IUDX (Indian Urben Data Exchange) Link Whitepaper Link
Aksah Ravi (gnani) talked about NLP based voice assistant products that supports Hindi, Kannada etc.
Out of all AI/ML projects hardly 13 to 14 % projects are successful and only 8% of customer are happy. Some projects need their ML model to be updated every week, even every day. AI/ML business case is all about identifying and satisfying unmet and unmentioned need. Few challenges (1) AI/ML implementation needs cultural change, where man and machine both work together. (2) upskill of existing staff (3) Data is fuel for AI. More time goes to find out which data to use rather than building AI/ML model. Noise in data can cause bias. The chatbot may learn offensive language over time. (4) explain-ability of AI/ML outcome. (5) Robust governance is also important. At present, chatbots are becoming popular. Long way to go. Information architecture (IA) is must for AI/ML projects. IA is the structural design of shared information environments.
Queryplex and federation are effective tools from IBM to connect multiple data sources. AI OpenScale is another tool from IBM
Ashok Ayengar talked about shopx - buy and sale platform.
Last 25 years of history big enterprise adopted new technologies like ERP and small stratup companies built eco-system around it. Many fortune 500 companies have huge legacy in range of 20 to 100 years. They need machine learning even on end-of-life servers.
The collaboration at Bangalore is not seen even in developed country. Here we have hackathon, open source contribution, discussion at physical meetup etc. It is really proud to be in Bangalore.
The day 1 ended with thought leaders conclave on "TechScape 2035"
The following trends are emerged.
1. Digitalization
2. Rapid Urbanization
3. Customer does not want product, but wants solution
4. so more and more collaborations
The growth of Internet was not predicated.
1. Growth with many IoT devices
2. Growth for amusement e.g. Netflix
3. Many networks E.g. Car has many networks
During 90s, when Internet based innovative services and business was planned, no one predicated that everyone (4 billion people) will have smart phone. Now cost of computing come down. Technology is democratized. This growth will be accelerated further, as everything (e.g. speaker, light etc.) will have compute power, connectivity, intelligent (AI/ML). The enormous data is generated by our wearable. Evolution will happen in laboratory and new human being will be created. Excitement with fear.
Now the smart software makes diagnosis smarter than doctor. In next 5 to 10 years, it will be mandatory to take second opinion from machines. People will get incentive for not being sick by health insurance and hospitals. The Indian doctors and nurses are best in the world. This is a license driven industry.
Now in automobile people need : 0 emission, 0 downtime, 0 accident, and first solution is electric car. Electricity is alternate fuel. The omnipresent 3D printing will eliminate need to keep inventory of spare parts of cars. The digitization, GST have improved logistics a lot. We need more efficiency steps like: spare trailers will just replace the loaded one to save time.
All these trends will empower the bottom of pyramid, surprisingly.
In future, there is no concept of firm. All companies are becoming platform. Apple started as platform for iOS apps. People starts company just on WhatsApp group. Now we will see rapid consolidation of firms. So monopoly will be back.
The present generation is Digital Native and generation Z Their working style is completely different.
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