Showing posts with label Innovation. Show all posts
Showing posts with label Innovation. Show all posts
Bengaluru Tech Summit : Day 3 - Part 2
Next panel discussion was on "Society 5.0 : Moving towards smart society by Japan". The investment in infrastructure projects needs patience, while US investors are impatients. So Japan is better choice with its excess capital. In Bangalore, all metro project, sewage project etc infrastructure projects are funded by Japan. Human species evolved from hunting to agriculture to industry revolution. Japan had huge contribution during the industry revolution with its unique quality processes/tools etc. Even today they are applicable in software/IT industry as DevOps practices. India's strength is neither manufacturing nor hardware. India strength is knowledge. Its skilled, English speaking manpower in knowledge driven industry of today's. India also has massive data for machine learning of around 1.2 billion UID. China has even more data, but under full control of government, so no use. "Bengaluru Tokyo Technology Initiative" is worth to explore. Bangalore is hub for technology, efficiency and entrepreneurship. Japan welcomes Indians.
Dolphin tank is an interesting initiative at Bangalore. It proposes to mentor and guide the start-ups through the next stage of journey for 6 months. Just like the dolphin who is a friend in the ocean, Dolphin guides the person through the journey in the rough sea till the person becomes independent. India had cost arbitrage earlier, now India has skill arbitrage. Large organisations depends on India for innovation. Now such organisation does not increase head count at Indian center. They effectively utilizes the startup ecosystem of India.
Panel discussion about "Decoding industry 4.0 and digitization: from vision to reality by Germany". Today if one cannot learn, unlearn and relearn then he/she is illiterate. There will be 200 billion devices by year 2025. There are four pillars of IoT:
1. Hardware,
2. Extremely complex algorithms,
3. Software = Algorithm + data. Software takes action based on them.
4. Cyber Security.
It requires risk taking attitude for testing and trial for IoT project. German has more corporate culture. An average German person is skillful in analog, slow and perfect in engineering. While India has startup culture, risk taking attitude, software skill etc. So both are supplementary to each other.
The industry 4.0 revolution is happening right now. There is no time of 8 years of fundamental research. The capable heavy industry needs supports from SMEs for smart factories. Today with AR and VR, one can get feel of being in middle of dangerous machine, aviation and heavy sector. All regions of world has different lead time to manufacture IC in small quantity. China/Tiwan never accept order in small quantity. German quotes high price with long delivery time. The IoT and Industry 4.0 revolution is happening now, here in college curriculum. During QA, three challenges for startups were discussed:
1. Skillset
2. Finance
3. Scalability
"Who is better? A German leader or Modi?" "Nelson Mandela."
It is possible to write book / biography by "ghost writer" using NLP based software.
Panel discussion about "Geospatial innovations in the times of disruptive changes by KSRSAC" Karnataka Geographic Information System is worth to explore. Geospatial analysis and deep learning based GeoAI are also interesting fields. Bharat Lohani explains, how his company Geokno use LiDAR technology to capture data. They cover 300 square km per day. They have developed alogrihtms, that can detect terrain even in dense forest. They can detect wild creatures in forest. they can detect water channel, very useful to divide water between two states and to help better irrigation. They can create 3d maps. The shadow analysis throughout a day, is very useful for establishing solar energy plant. One more interesting talk by Laxmi Prasad Putta from Vassar Labs.
Panel discussion about " Emerging Technologies areas in the Indic language-technology Industry by FICCI". Vivekanand Pani talked about his company Reverie Language Technologies's product "Gopal". It is a virtual assistant that can speak many Indian languages. Thirumalai Anandanpillai mentioned that Microsfot's Azure cloud exposes we service API for speech to text for Indian languages. Vinay Chhajlani's WebDunia.com turns 19 years old company in September 2018, who survived through dot com boom. In 2014, DNS was supporting 15 different languages. In 2019, Kannada will be also added in DNS, that is called IDN (International Domain Name). In the world 20 % people knows English and in India 12 % people knows English. So IDN is needed for non-English domain name. On 1st May 2018, a legal framework for Indic language was established. Since 2014 Gmail supports IDN based e-mail addresses. 4 million users uses Hindi email address by Rajsthan Government. Today more Internet data traffic is about entertainment content. However it will change, as government will give more online services in regional languages. The emerging opportunity is driving emerging of technology. In year 2010, VCs thought that Indian language speaking customers has no money so they were reluctant to invest for such language based startups. 22 years ago, we had only 1 % of PC penetration, so no need of Hindi. In 2010, 50% of mobile penetration, so Hindi was needed. So in 2011, first mobile phone launched with Hindi supports. Today many people are first time Internet user with mobile. In 2002, the way people were behaving at Yahoo chat room, today this first time user may behave same way.
During QA, I asked about Sanskrit, Sage Panini's Sanskrit grammar and its relevant with NLP. Everyone nominated Thirumalai Anandanpillai from Microsoft to answer the question. May be because he has nice TILAK on his forehead. He replied, that today translation happens by Neural Network. It is not rule based. Panini's grammar is relevant and useful for rule based services.
So overall "Bengaluru Tech Summit" was worth to attend event, with many thought provoking ideas, updates about recent trends, startups and insight to upcoming futures. There was also exhibition with stalls from established companies and startups both.
Dolphin tank is an interesting initiative at Bangalore. It proposes to mentor and guide the start-ups through the next stage of journey for 6 months. Just like the dolphin who is a friend in the ocean, Dolphin guides the person through the journey in the rough sea till the person becomes independent. India had cost arbitrage earlier, now India has skill arbitrage. Large organisations depends on India for innovation. Now such organisation does not increase head count at Indian center. They effectively utilizes the startup ecosystem of India.
Panel discussion about "Decoding industry 4.0 and digitization: from vision to reality by Germany". Today if one cannot learn, unlearn and relearn then he/she is illiterate. There will be 200 billion devices by year 2025. There are four pillars of IoT:
1. Hardware,
2. Extremely complex algorithms,
3. Software = Algorithm + data. Software takes action based on them.
4. Cyber Security.
It requires risk taking attitude for testing and trial for IoT project. German has more corporate culture. An average German person is skillful in analog, slow and perfect in engineering. While India has startup culture, risk taking attitude, software skill etc. So both are supplementary to each other.
The industry 4.0 revolution is happening right now. There is no time of 8 years of fundamental research. The capable heavy industry needs supports from SMEs for smart factories. Today with AR and VR, one can get feel of being in middle of dangerous machine, aviation and heavy sector. All regions of world has different lead time to manufacture IC in small quantity. China/Tiwan never accept order in small quantity. German quotes high price with long delivery time. The IoT and Industry 4.0 revolution is happening now, here in college curriculum. During QA, three challenges for startups were discussed:
1. Skillset
2. Finance
3. Scalability
"Who is better? A German leader or Modi?" "Nelson Mandela."
It is possible to write book / biography by "ghost writer" using NLP based software.
Panel discussion about "Geospatial innovations in the times of disruptive changes by KSRSAC" Karnataka Geographic Information System is worth to explore. Geospatial analysis and deep learning based GeoAI are also interesting fields. Bharat Lohani explains, how his company Geokno use LiDAR technology to capture data. They cover 300 square km per day. They have developed alogrihtms, that can detect terrain even in dense forest. They can detect wild creatures in forest. they can detect water channel, very useful to divide water between two states and to help better irrigation. They can create 3d maps. The shadow analysis throughout a day, is very useful for establishing solar energy plant. One more interesting talk by Laxmi Prasad Putta from Vassar Labs.
Panel discussion about " Emerging Technologies areas in the Indic language-technology Industry by FICCI". Vivekanand Pani talked about his company Reverie Language Technologies's product "Gopal". It is a virtual assistant that can speak many Indian languages. Thirumalai Anandanpillai mentioned that Microsfot's Azure cloud exposes we service API for speech to text for Indian languages. Vinay Chhajlani's WebDunia.com turns 19 years old company in September 2018, who survived through dot com boom. In 2014, DNS was supporting 15 different languages. In 2019, Kannada will be also added in DNS, that is called IDN (International Domain Name). In the world 20 % people knows English and in India 12 % people knows English. So IDN is needed for non-English domain name. On 1st May 2018, a legal framework for Indic language was established. Since 2014 Gmail supports IDN based e-mail addresses. 4 million users uses Hindi email address by Rajsthan Government. Today more Internet data traffic is about entertainment content. However it will change, as government will give more online services in regional languages. The emerging opportunity is driving emerging of technology. In year 2010, VCs thought that Indian language speaking customers has no money so they were reluctant to invest for such language based startups. 22 years ago, we had only 1 % of PC penetration, so no need of Hindi. In 2010, 50% of mobile penetration, so Hindi was needed. So in 2011, first mobile phone launched with Hindi supports. Today many people are first time Internet user with mobile. In 2002, the way people were behaving at Yahoo chat room, today this first time user may behave same way.
During QA, I asked about Sanskrit, Sage Panini's Sanskrit grammar and its relevant with NLP. Everyone nominated Thirumalai Anandanpillai from Microsoft to answer the question. May be because he has nice TILAK on his forehead. He replied, that today translation happens by Neural Network. It is not rule based. Panini's grammar is relevant and useful for rule based services.
So overall "Bengaluru Tech Summit" was worth to attend event, with many thought provoking ideas, updates about recent trends, startups and insight to upcoming futures. There was also exhibition with stalls from established companies and startups both.
Bengaluru Tech Summit : Day 3 - Part 1
We had interesting panel discussion on the topic Innovations driving next generation enterprise
Trends
* Now, the personal computing is more affordable compare to 1960s and 1980s due to to reduction is computing cost, storage cose and emergence of open source culture.
* In 1990s all the computers are interconnected and the Internet emerged along with new business models for finance/banking, retail e-commerce and e-mail. New enterprises also got emerged. Today we are living in digital age or mobile age.
* The people who born around 1995, have entered as work force around 2015. Generation Z, how to influence these 2 billion people, with different set of expectations.
* IoT
* Emergence of rural area. Now rural people also have access to information.
* Now people feel pride to work at startups.
* A new startup can be started just using WhatsApp groups.
* Supportive governments and Law. Few examples of few funny laws, that exist even today. Laws are reaction to 150 years of industrial revolution. The government should not stop the growth. So Karnatak is first state in India with regulatory sandbox, where you are allowed to break (only state) law for duration ranges from 3 months to 2 years, powered by Karnataka Innovation Authority. More can be achieve on startup front with de-regularization like allowing crypto currency.
* All the new innovations are becoming necessities.
* Big giant companies like IBM are supporting startups by finance, by connecting them to large customer base, scaling up. They cannot continue with their own R&D center so they come to startups. Block chain based virtual idea market may emerged in next few months.
* Online transactions will ultimately eliminate the need for banks.
* Education: 500 Mbps bandwidth at each home, will eliminate universities. all students will study online. Then even 6th standard students will talk about Artificial Intelligence, Machine Learning, IoT, Block Chain etc.
* The rule based and law based audit will change. Already after GST and demonetization the B.Com degree has more value compare to BBA or BBM. Now working people need to play different roles to remain in job market. Innovations at large enterprises are reducing jobs. On the other hand, same innovation increases the jobs at startups.
The factors that drives innovations are changed based on above trends. The generation z is consumer as well as is at startups, so disruption is bound to happen. Now all enterprise needs innovation to survive or to make more profit in areas of their products, service and/or process.
Discovery v/s Invention v/s Innovation
We know discovery is about something that already exists. Invention is one step further, by combining multiple few discoveries. Innovation goes even further by combining multiple inventions and build a use case to satisfy needs. The startups are all about building faster, better, cheaper solutions with help of inventions. Today major innovations are around (1) Artificial Intelligence, (2) data science and (3) block chain. Again startups need to focus on usage rather than the technology. 90% of startups fail due to lecuna about how to take it forward. All entrepreneurs cannot scale up their venture. Startups are risky, but design driven approach, reduces the risk.
It is not important, what you study (in college/school to get your degree). The important aspect is what you continue to study. Today everyone should know, how to learn new topics, unlearn old topics and re-learn as per emerging trends.
Bengaluru Tech Summit : Day 2
There was an interesting experiment on a patient, who daily forgets her past life. Everyday, she introduce herself, shake hands like meeting for the first time. The scientist doctor, started hurting her with small pin, during shake hand. Just in few days, she stopped shake hands with the scientist, even though she could not recover any memory associated about him. There are many research on topics of fear, fact, emotions, memory etc.
Brain Research in the age of information technology
As per Moravec's paradox, what we human beings find very easy is difficult for computers and what is easy for computers, that we find the most difficult. Like computer compare two images, pixel by pixel and so it cannot identify two objects are same, if the images are from different angle. On other way, two images of up-side-down faces, we human beings find identical, but when we rotate 180 degree, we realize they are different. It is easy for computer to tell, that they are different, as it compare pixel by pixel. Today 80 % of object detection is done by AI/ML.The 40% of our brain are is involved in visual processing. The brains does not look at brightness of pixel. We also discussed about famous image, about a dress, where a group people says white and blue, while others say gold and black. The color depends on individual perception about color of light falling on that dress white or yellow. Symmetry in deep learning network, increases accuracy from 1 to 10 %. Few initiatives:
* OpenAI is a non-profit AI research company, discovering and enacting the path to safe artificial general intelligence. Many projects by OpenAI on github.
* VisionLab@IISc, Bangalore. Website and Facebook page
Ashwini Godbole emphasize on trans-disciplinary approach of brain health as per Ayurveda and modern biomedicine for brain. She also explained about clinic to lab approach. She mentioend about meaningful eating.
Brain Research in the age of information technology
As per Moravec's paradox, what we human beings find very easy is difficult for computers and what is easy for computers, that we find the most difficult. Like computer compare two images, pixel by pixel and so it cannot identify two objects are same, if the images are from different angle. On other way, two images of up-side-down faces, we human beings find identical, but when we rotate 180 degree, we realize they are different. It is easy for computer to tell, that they are different, as it compare pixel by pixel. Today 80 % of object detection is done by AI/ML.The 40% of our brain are is involved in visual processing. The brains does not look at brightness of pixel. We also discussed about famous image, about a dress, where a group people says white and blue, while others say gold and black. The color depends on individual perception about color of light falling on that dress white or yellow. Symmetry in deep learning network, increases accuracy from 1 to 10 %. Few initiatives:
* OpenAI is a non-profit AI research company, discovering and enacting the path to safe artificial general intelligence. Many projects by OpenAI on github.
* VisionLab@IISc, Bangalore. Website and Facebook page
Ashwini Godbole emphasize on trans-disciplinary approach of brain health as per Ayurveda and modern biomedicine for brain. She also explained about clinic to lab approach. She mentioend about meaningful eating.
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.
AI/ML for SMB
1. Salesforce : Einstein AI Intelligent CRM
2. MailChimp : Email
marketing
3. Clare.AIClare.AI is
an example of a plug and play app for (1) online banking services,
and (2) to handle a larger volume of customer inquiries without hiring more
staff.
4. Malaysian company, Supahands for
upwork like service to select crowd sourcing v/s freelancer
5.
smart speaker or home robot can be used at retail outlet
6. Digital Genius : Intelligent customer service
query. The AI platform for customer service
7. Acquisio : online ads on Facebook, Bing, Adwords
8. Darktrace : Data security. Enterprise Immune System technology for cyber security.
9. Crayon : Competitor analysis
10. Aivo : chat bot
12. Datorama: end to end marketing integration platform
13. VoxPro multilingual customer experience and
technical support solutions
14. bold360 Better customer engagement
15.
call center
16.
SAP CoPilot: Digital Assistant in the Enterprise
18. AISense: Call, Meeting Transcriptions
19. WalkMe: AI for Software Training. Integrated with Athenahealth,
Salesforce, Workday etc.
20.
Workday: Finance and HR
21.
Athenahealth uses WalkMe to train
doctor, nurse about how to use system
22.
ServiceChannel for restaurants
23.
Niles for conversation
24. MESH, Not Rocket Science:
Branded Bots
25.
Acculation Social Media content
decision.
Reference:
1. https://www.salesforce.com/blog/2016/09/introducing-salesforce-einstein.html
2. https://www.cmswire.com/information-management/6-ways-artificial-intelligence-will-impact-the-future-workplace/
5. https://www.cmswire.com/digital-workplace/8-examples-of-artificial-intelligence-ai-in-the-workplace/
MLCC
Let me share key take away points from meetup event "Google Machine Learning Study Jam"
In Feb/March 2018, Google announced MLCC Machine Learning crash course In July 2018, MLCC Study Jam series comes to India. Click here and click here to know more. I attended one such event with my friend, by Industry 5.0 meetup.
Here are few useful links
TensorFlow Content Bundle, Spring 2018
Gradients and Partial Derivatives : YouTube Video
Later on, I found the Maths play list is good. All videos by Eugene Khutoryansky are excellent
Another YouTube video by Christopher Gondek. Here also, the playlist about 'Machine Learning Visualization' is good.
In Feb/March 2018, Google announced MLCC Machine Learning crash course In July 2018, MLCC Study Jam series comes to India. Click here and click here to know more. I attended one such event with my friend, by Industry 5.0 meetup.
Here are few useful links
TensorFlow Content Bundle, Spring 2018
Gradients and Partial Derivatives : YouTube Video
Later on, I found the Maths play list is good. All videos by Eugene Khutoryansky are excellent
Another YouTube video by Christopher Gondek. Here also, the playlist about 'Machine Learning Visualization' is good.
Microsoft announced about FPGA based Edge Computing : Brainwave project
AutoML and transfer learning. At present, they are at nascent stage. Once let it fully evolved then we may not need people who know AI/ML. The machine themselves will learn. I did little Googling and found few links : http://www.ml4aad.org/automl/ and https://automl.info/
As per my knowledge, after completing any Machine Learning course till one completely switch his/her career path, Kaggle is the only platform to get hands-on experience. I came to know one more such platform Seedbank I found one seed about 'Piano Transcription' quite interesting. We discussed with Sanjay Chitnis about creating similar seed to recognize Indian Raga
There is an interesting book 'Pattern Recognition and Machine Learning (Information Science and Statistics)' by Chrisopher M. Bishop
http://playground.tensorflow.org is an excellent, browser based Neural network tool. It is also used as part of MLCC We discussed about L1 regularization, L2 regularization, confusion matrix, precision, accuracy, recall, F1 score, Receiver operating characteristic etc. Precision is all about how many positive case, the algorithm could able to detect out of all positive cases. Recall is about how good is the diagnostic test?
CNN is combination of filter and dimension reduction. RNN is a special case of LSTM. GAN is widely used to creation. The GAN Zoo has list of all variations of GAN
We also discussed about Semi-Supervised Learning , Topic Learning OR Keyword Learning, that is beyond supervised learning, Gold standard etc.
At the end, Sanjay drew out attention to an interesting trend that now, product cost is keep reducing. Features in products are keep increasing. Service cost is keep increasing ! India has lots of data available. There is good scope of data analytics and machine learning for General Election 2019 at India.
OpenStack meetup
16th June 2018, I attended OpenStack Meetup at Ericsson office. Let me share my notes for readers of this blog : Express YourSelf !
Shashi Singh from Altiostar Networks discussed about EPA (Enhanced Platform Awareness).
EPA is about about making aware NFVO, VNFM and VIM, that specialized hardware is available below virtualization layer. E.g. High I/O throughput, high performance CPU, GPU, crupto accelerators and many more as below slides:
Shashi explained nicely NFV MANO architecture to build the context and introducing the acronmys. Telco NFVI providers are: RedHat, WindRiver, VMWare, Mirantis etc. VNFM is categorized as specific VNFM and Generic VNFM. It supports three interfaces: Ve-Vnfm-vnf, Vi-Vnfm and Or-Vnfm.
He explained how EPA can eliminate the need of passing through virtualization layer for data packet, if the required VNFs are running at same CPU socket. I confirmed my understanding that, one example of EPA is let all VNFs for user-plane data having single CPU afinity. We also discussed about SR-IOV single root input/output virtualization, cpu pinning, threading policy etc. Sometimes within storage node, one can leaverage use of SR-IOV, DPDK etc to support more I/O. TOSCA standard defines combination of NS-D (Network Service Descriptor) and VNFD (VNF Descriptor). Shashi also mentioend about Queens Release, Cyborg framework, nova, ironic etc.
Here is list of Intel technologies for EPA
1. Intel Advance Encryption Standard - New Instructions (Intel AES-NI)
2. Intel Advance Vector Extensions (AVE) and AVE2
3. Intel Quick Sync Video Technology
4. Intel QuickAssist Technology for encryption / decryption and compression / decompression
5. Intel Trusted Execution Technology (TXT)
6. Intel Node Manager : Server Mangement at Data Center
7. Data Plane Development Kit (DPDK) at Xenon processor
8. SR-IOV
9. Intel Xeon Phi Co-processor: for PCI
I came to know about this website https://www.telecomtv.com/ During tea-break, someone commented, that Kubernetes is now open source, but it is very old. Google is working on new technology / product named by Omega that is yet to be open sourced.
Palaniswamy from Tech M, explains about ManageIQ (with demostration) as Multi Cloud Management Platform. ManageIQ supports public clouds like : Amazon Web Services, Microsoft Azure, Google Cloud Platform; OpenStack based private clouds; containers like Kubernetes, OpenShift Origin etc. ManageIQ internally uses PostgreSQL DB. Ansible Tower is used for configuration and automation.
Sukant J R and Manoranjan Sahoo from Ericsson presented about CI/CD for containerized openstack development based on Helm.
We also discussed about 4 types of people in IT industry always remains. (1) Developers (2) Support engineers (3) Integrators and (4) Testers. The new technology comes and goes. One needs to work, as per his/her core strength.
Apart from that, Uday T.Kumar from Ericsson shared some insights about OpenStack Summit and how to contribute to OpenStack community. He also acknowledged that Bangalore OpenStack community is very active and sharing the latest updates. Later on those updates are known to entire world at OpenStack summit.
Disclaimer: I captured this notes, as per my understanding on best effor basis. So it may not accurately refelct the spearker's view. Any corrections are welcome.
Reference:
https://www.meetup.com/Indian-OpenStack-User-Group/events/249891291/
https://01.org/sites/default/files/page/openstack-epa_wp_fin.pdf
https://networkbuilders.intel.com/network-technologies/enhancedplatformawareness
Shashi Singh from Altiostar Networks discussed about EPA (Enhanced Platform Awareness).
EPA is about about making aware NFVO, VNFM and VIM, that specialized hardware is available below virtualization layer. E.g. High I/O throughput, high performance CPU, GPU, crupto accelerators and many more as below slides:
Shashi explained nicely NFV MANO architecture to build the context and introducing the acronmys. Telco NFVI providers are: RedHat, WindRiver, VMWare, Mirantis etc. VNFM is categorized as specific VNFM and Generic VNFM. It supports three interfaces: Ve-Vnfm-vnf, Vi-Vnfm and Or-Vnfm.
He explained how EPA can eliminate the need of passing through virtualization layer for data packet, if the required VNFs are running at same CPU socket. I confirmed my understanding that, one example of EPA is let all VNFs for user-plane data having single CPU afinity. We also discussed about SR-IOV single root input/output virtualization, cpu pinning, threading policy etc. Sometimes within storage node, one can leaverage use of SR-IOV, DPDK etc to support more I/O. TOSCA standard defines combination of NS-D (Network Service Descriptor) and VNFD (VNF Descriptor). Shashi also mentioend about Queens Release, Cyborg framework, nova, ironic etc.
Here is list of Intel technologies for EPA
1. Intel Advance Encryption Standard - New Instructions (Intel AES-NI)
2. Intel Advance Vector Extensions (AVE) and AVE2
3. Intel Quick Sync Video Technology
4. Intel QuickAssist Technology for encryption / decryption and compression / decompression
5. Intel Trusted Execution Technology (TXT)
6. Intel Node Manager : Server Mangement at Data Center
7. Data Plane Development Kit (DPDK) at Xenon processor
8. SR-IOV
9. Intel Xeon Phi Co-processor: for PCI
I came to know about this website https://www.telecomtv.com/ During tea-break, someone commented, that Kubernetes is now open source, but it is very old. Google is working on new technology / product named by Omega that is yet to be open sourced.
Palaniswamy from Tech M, explains about ManageIQ (with demostration) as Multi Cloud Management Platform. ManageIQ supports public clouds like : Amazon Web Services, Microsoft Azure, Google Cloud Platform; OpenStack based private clouds; containers like Kubernetes, OpenShift Origin etc. ManageIQ internally uses PostgreSQL DB. Ansible Tower is used for configuration and automation.
Sukant J R and Manoranjan Sahoo from Ericsson presented about CI/CD for containerized openstack development based on Helm.
We also discussed about 4 types of people in IT industry always remains. (1) Developers (2) Support engineers (3) Integrators and (4) Testers. The new technology comes and goes. One needs to work, as per his/her core strength.
Apart from that, Uday T.Kumar from Ericsson shared some insights about OpenStack Summit and how to contribute to OpenStack community. He also acknowledged that Bangalore OpenStack community is very active and sharing the latest updates. Later on those updates are known to entire world at OpenStack summit.
Disclaimer: I captured this notes, as per my understanding on best effor basis. So it may not accurately refelct the spearker's view. Any corrections are welcome.
Reference:
https://www.meetup.com/Indian-OpenStack-User-Group/events/249891291/
https://01.org/sites/default/files/page/openstack-epa_wp_fin.pdf
https://networkbuilders.intel.com/network-technologies/enhancedplatformawareness
5G NR : Part 1
5G is about IoT. In fact in 4G also, IoT related standardization was started with NB-IoT.
Use Cases
Use Cases
- AR/VR
- Autonomous transportation (car)
- Reliable access to remote health-care
- Public safety
- Smarter Agriculture
- Efficient use of energy/utilities
- Autonomous manufacturing
- Sustainable cities and infrastructure
- Digitized logistics and retails
Verticals
Market Segments
1. Enhanced Mobile Broadband (eMBB)
2. Massive Machine Type Communications (eMTC)
3. Ultra Reliable and Low Latency Communications (URLLC)
Key KPIs
1. Peak data rate
2. Spectrum efficiency
3. Mobility
4. Latency
5. Connection diversity
6. Network energy efficiency
7. Area traffic capacity
5G standard bodies
1. 3GPP (ITU-R) : (IMT 2020)
2. EU - (METIS - 2020)
3.1 Japan 2020 and beyond
3.2 Korea 5G Forum
3.3 MOST - China
5G Evolution
1. IMT-Advanced
2. Enhanced IMT-Advanced
3. 5G RAN
Peak data rate
Mobility
Capacity (/km square)
Number of connected devices / cell
User plane latency
Energy Saving (energy / bit)
5G Standards
pre 5G standard - https://m.corp.kt.com/eng/html/biz/services/sig.html
3GPP Important Standards
TS 38.211 NR; Physical channels and modulation
TS 38.212 NR; Multiplexing and channel coding
TS 38.213 NR; Physical layer procedures for control
TS 38.214 NR; Physical layer procedures for data
TS 38.215 NR; Physical layer measurements
TS 38.300 NR; Overall description; Stage-2
TS 38.321 NR; Medium Access Control (MAC) protocol specification
TS 38.322 NR; Radio Link Control (RLC) protocol specification
TS 38.323 NR; Packet Data Convergence Protocol (PDCP) specification
TS 38.331 NR; Radio Resource Control (RRC); Protocol specification
TR 38.801 Study on new radio access technology: Radio access architecture and interfaces
TR 38.912 Study on new radio access technology
TR 38.913 Study on scenarios and requirements for next generation access technologies
TS 23.501 System Architecture for the 5G System
NSA
gNB to EPC
SA
gNB to 5G CN
For greenfield deployment
4G and 5G comparison
U-Plane
New protocol SDAP over existing PDCP
Deployment Models
Reference : TR 38.913 Study on scenarios and requirements for next generation access technologies
mmWave frequency is > 30 GHz
5G New Technology
1. mmWave frequency is > 30 GHz
2. Massive MIMO > 8 x 8 MIMO
3. Beam Management
4. LDPC coding (for U-Plane) and Polar coding (for C-Plane)
5. AS Layer
6. UL Waveform
7. Subframe structure
8. HARQ
9. SDN
10. NFV
11. Grant-free UL for IoT
Numerologies
1 frame = 10 subframe
1 subframe's slot = f (n)
1 slot = 14 symbols
So 1 frame's slot = 10 x f(n)
So 1 subframe's symbols = 14 x f(n)
So 1 frame's symbol = 10 x 14 x f(n) = 140 x f(n)
Slot Format
TDD or FDD depends upon
0 : All 14 Symbols are D
1 : All 14 Symbols are U
2 : X
3 : 13 D + 1 X
4: 12 D + 2 X
5 : 11 D + 3 X
D = Downlink
U = Uplink
X = Flexible
To be continued...
