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Millions of innovative tech ideas come up every year that can revolutionize industries and enhance human lives. These ideas emerge with a promise that could change the world if the right people work on it, and importantly, they get financial backing. However, a substantial portion of these ideas fail to make their way into the consumer's hands due to the lack of funding. Despite their potential to reshape the future, many innovative concepts fail to impress , thus unable to secure grants for their execution. investors Addressing the deficit in funding allocated for innovative ideas is a challenge that necessitates our attention and concerted efforts. Keeping that in mind, the Indian Government has taken the initiative to help the young geniuses of the country. In her Union Budget 2024 presentation today, on February 1, Finance Minister Nirmala Sitharaman highlighted a promising outlook for the tech-savvy youth, stating that "this will be a golden era" for them. Finance Minister Sitharaman said, "For our tech-savvy youth, this will be a golden era. A corpus of Rs 1 lakh crore will be established with a 50-year interest-free loan provided. It will be for long-term financing or re-financing with low or nil interest rates." "We need to have programs that combine the powers of our youth and technology," the minister added. Finance Minister Sitharaman also announced that a new scheme will be launched "for strengthening deep-tech technologies for defence purposes and expediting 'atmanirbharta'." Speaking on new-age tech, Sitharaman said, "New-age technologies and data are changing the lives of people and businesses. They are also enabling new economic opportunities and facilitating the provision of high-quality services at affordable prices for all, including those at the ‘bottom of the pyramid.’" She also expressed her gladness about the fact that India is leading the way in "showing solutions through innovation and entrepreneurship of its people." She added that opportunities for India and its citizens are expanding at the global level. India is expected to surpass Japan and become the third-largest economy by the year 2030. The tech startups will play a major role in bringing Foreign Direct Investments into the country and generating employment for India's massive population of 1.4 billion people. The difficulty in convincing investors is one of the biggest issues faced by tech startups in developing countries like India and Vietnam. Some of India's startups rank in the top tier around the world in their respective fields and thus, have successfully created a reputation of Indian companies. In the Financial year 2022-2023, the total Foreign Direct Investment was $70.97 Billion, and total FDI equity inflows stood at $46.03 Billion. The Service and the Computer Software and Hardware sectors received the highest FDI of 16% and 15%, respectively. There have been many cases where a small startup was not able to expand due to the insecurities of the existing investors and their reluctance to take bold steps, but despite the restraints, the Indian entrepreneurs were able to bring their ideas into reality. They were able to bring products to the market which helped the people and also were profitable. Also published here

How India's New Budget is Helping Foster Innovative Ideas

Phishing and fraudulent emails are on the rise and continue to be major problems for both businesses and consumers. It has become a must for brands to adopt security measures and make it a safe and reliable journey for their customers. Having DMARC, DKIM, and SPF in place, businesses are adopting BIMI, a relatively new authentication standard for another layer of protection. It’s the only visual assistance out of all the other verification methods, helping your recipients identify that your messages are coming from an authentic and legitimate source. BIMI is a great way to build trust in email communication and help avoid phishing. In this article, we will delve into the details of this authentication standard and cover its step-by-step implementation process. What Is BIMI? BIMI, or Brand Indicators for Message Identification, is an email standard that attaches your brand logo to authenticated messages sent from your domain. In other words, it allows you to display the logo next to the email in the recipients’ inboxes. This kind of visual verification helps your users instantly recognize your emails and be more confident in opening them. https://www.youtube.com/watch?v=LjtGwsWDNDY&t=87s&embedable=true Like DMARC, DKIM, and SPF, BIMI is a text record that works by allowing you to publish it in your DNS. The record consists of secure URLs to your logo and your VMC (Verified Mark Certificate, required only by Gmail): v = BIMI1; l = https://example.com/logo.svg; a=https://example.com/certificate.pem When your email is delivered to a BIMI-supported provider, it checks your DMARC policy and retrieves your BIMI text record. Once your logo is found, the mailbox provider will attach it to your email in the recipient’s inbox. Which Mailbox Providers Support BIMI? As far as BIMI, it’s a relatively new email authentication standard; only some inbox providers are supporting it. Here is the list of mailbox providers that support BIMI according to the : BIMI group Inbox providers supporting BIMI: Apple Mail Cloudmark Fastmail Google Gmail La Poste Onet Poczta Yahoo! Zone Inbox providers considering BIMI: Atmail BT Comcast Qualitia Seznam.cz Gmx Yahoo! Japan An Inbox provider not supporting BIMI: Microsoft How BIMI Works: The Main Requirements and Set-up Process BIMI implementation seems complicated and intimidating, especially for businesses new to email authentication standards and just starting to adopt these security measures. But we’ll try to walk you through some of the steps that you need to take to set up BIMI correctly: BIMI works only for domains that are already DMARC compliant and have achieved p=quarantine or p=reject. You can check out for detailed information and everything-DMARC. Achieve DMARC enforcement: this guide BIMI uses this certificate to make sure you have ownership over your logo. This step is optional for mailbox providers and is only required for Gmail. We’ll cover more about this in the next section. Acquire a Verified Mark Certificate (VMC): Make sure you have your brand’s logo located at a secure URL in SVG format. Create a secure URL for your logo: Make sure you have your VMC located at a secure URL in .pem file format. Create a secure URL to your VMC: Now that you have completed all the previous steps, you can generate the BIMI record, and add this TXT record to your domain provider's management console. You can use our free for easier implementation: Generate a BIMI record: BIMI record generator tool To check if your domain uses BIMI, use our free lookup tool and see if your record meets the requirements. Check for an existing record: This is the overall process of setting up BIMI. If you are not experienced in IT or work as an email administrator, this process may be too technical for you. You can contact us any time to help you set up BIMI for your organization. Now, let’s jump to VMC and fully understand its requirements. Introduction to VMC As you noticed, for a proper BIMI implementation, VMC or a verified Mark Certificate is a must for . VMC is a certificate that verifies that you are the legal owner of your logo and have the right to display it next to your emails in the inbox. mailbox providers like Gmail Using your logo with this certificate makes it harder to spoof, as it’s verified by the trademark organization. Now, let’s go through the step-by-step process of acquiring VMC: Become DMARC compliant Just like BIMI, for VMC, is compulsory. This is the first and most important step in not only acquiring the certificate but also adopting BIMI as an email authentication standard. becoming DMARC compliant Trademark your logo Next, you need to register your brand logo as a trademark in an intellectual property office or make sure that it’s already trademarked. Currently, this step is required to qualify for VMC. However, in the future, the standard may expand and include not-registered logos as well. Ensure your logo is formatted correctly Before applying for the certificate, ensure that your logo is in a proper .svg format. Register for the certificate Contact or Entrust certificate authority to request your VMC. By the way, we have partnered with DigiCert to make the BIMI implementation easier and smoother for our customers. As soon as your request is approved, you’ll receive the Privacy Enhanced Mail __ __file. Upload it to your public web server, and you’re ready to go. DigiCert (PEM) What Does BIMI Mean For Your Business? The blue checkmark next to the verified users on social media is not something new, and we all know about the impact it has on us while interacting with such profiles. It’s similar to what we have here with emails, except this blue checkmark indicates that the domain owner has gone through email authentication processes and reached the DMARC “reject” policy. It helps recipients be sure that the email they just received comes from a legitimate source and is authenticated. As verification becomes widespread, more and more businesses are expected to adopt such measures. As a result, phishing emails and any attempt of impersonation will become even more obvious, and your users will instantly identify and ignore them. Now, let’s highlight some key benefits of adopting BIMI: Enhance Your Brand Value Proper BIMI implementation also means having DMARC, SPF, and DKIM authentication standards in place. This demonstrates your commitment to email security and how important it is for your brand to protect your customers and subscribers from cyber attacks. Build Trust As already mentioned above, BIMI builds trust in your email communication. It helps your consumers have confidence in engaging with your content and be sure that the messages are authenticated with DMARC. Increase Deliverability and Boost Marketing Campaigns With a verified BIMI logo, your emails stand out from the rest in the inbox. This not only encourages more open rates but also lowers the chance of being reported, marked as spam, or unsubscribed. Such metrics play an important role in enhanced email deliverability and more effective marketing campaigns. Creating a valid BIMI record and putting it into action may seem challenging at first. However, it’s becoming increasingly popular as phishing attacks continue to evolve. More and more brands are adopting this email authentication standard, making the safety and protection of their users a priority for them.

What Is BIMI: Your Verified Brand Logo Next to Your Email in The Inbox

BIMI কী: ইনবক্সে আপনার ইমেলের পাশে আপনার যাচাইকৃত ব্র্যান্ডের লোগো

Was ist BIMI: Ihr verifiziertes Markenlogo neben Ihrer E-Mail im Posteingang

¿Qué es BIMI? El logotipo de su marca verificada junto a su correo electrónico en la bandeja de entrada

Qu'est-ce que BIMI : le logo de votre marque vérifié à côté de votre e-mail dans la boîte de réception

BIMI क्या है: इनबॉक्स में आपके ईमेल के आगे आपका सत्यापित ब्रांड लोगो

BIMI とは: 受信トレイのメールの横にある認証済みのブランド ロゴ

BIMI란 무엇입니까? 받은 편지함의 이메일 옆에 확인된 브랜드 로고가 표시됩니다.

O que é BIMI: o logotipo da sua marca verificada ao lado do seu e-mail na caixa de entrada

Что такое BIMI: логотип вашего проверенного бренда рядом с вашим адресом электронной почты во входящих

BIMI Nedir: Gelen Kutunuzdaki E-postanızın Yanında Doğrulanmış Marka Logonuz

BIMI là gì: Logo thương hiệu đã được xác minh của bạn bên cạnh email của bạn trong hộp thư đến

什么是 BIMI：收件箱中电子邮件旁边的经过验证的品牌徽标

THE TRANSFORMATION OF THE LIBIDO. A POSSIBLE SOURCE OF PRIMITIVE HUMAN DISCOVERIES

“Good Heavens, these are not the people for me!”

Tolstoi brings us face to face with religion

Over the past 10 years, I’ve had the chance to meet with several company founders and top executives to discuss about their company growth, ambition and challenges. In 2021, what makes these companies successful is their focus on the people, which will probably be obvious to all of you. The most successful of them were taking the greatest care of their people and were also the most selective in their hiring process. Of course, there are some exceptions. If you look around you, you’ll always find organisations that treat people badly and are generating a lot of cash or vice versa. Yet, what struck me the most during these conversations is that beyond caring for their people, it’s their focus on organisational design as well as their governance that seemed to have the greatest impact. There was not a particular framework that made the difference; it was their willingness to find the best approach for their organisation and workers. Thanks to my degree and my 8+ years of experience in various company sizes and industries, I have the pleasure to help medium and large organisations redesign their operating model. Indeed, building and leading product departments gave me the benefit of interacting with all their departments. It also helped me identify the benefits and pitfalls of how certain companies operate. The topics below are, according to me, the ones you should consider when you define your organisation’s design and its operating model. Mission and Vision Are your company’s mission and vision well defined? Can everyone in your organisation understand it and feel their work will contribute to it? In many organisations, the mission and vision are not clearly defined. As a result, it’s difficult for people to understand the reasons behind certain decisions or why certain work is important. And even though the mission and vision are well defined, if your organisation isn’t designed appropriately, your key people won’t be able to embrace them or share them with their team. Values Values are pretty subtle and intrinsically linked to your mission and vision, but they differ in the way that values also live in the blood of your people. For example, if one of your core values is the personal development of people, how will you make sure that your organisation supports it? Who will be responsible to support such initiatives? Should personal development be the responsibility of the HR department or the line management? Your people will be the carriers of your company culture. As explained to me by several CEO having lived hyper growth, and having experienced it in myself, your organisation will evolve and if you don’t pay attention, at some point you won’t recognise yourself in your organisation, which may be a disaster for you and your company. HR - Reward, Recognition and… Firing I’ve always felt that hiring is easy. You create a job listing. You interview people and eventually select the best candidate. What comes after is much more difficult. In your company's current framework, do you have enough ways to reward your people and recognise their work? Many people often forget about this aspect and can be confronted with a situation where, at best, they only have two options to reward someone: promote them or give them a raise. This might be okay when your organisation is still new, but over time, if you don’t have more options, you can find yourself in a tricky situation. For example, one typical mistake is to give a CPO title to a product manager at the start of a venture because they’re a good worker. But the consequence of this kind of action can be a disaster. It’s one thing to lead a team of 3 to 5 developers; it’s another to run 3, 4, or 10 squads. What will you do if you need to hire someone with much more experience? Will you demote your employee? Fire them? Another typical mistake is the inability to fire people. As your organisation grows, you will have to redefine your operating model and not everyone will remain a good fit. At the beginning of a venture, you’ll look for very versatile people that can wear multiple hats, but as you grow, you’ll want to have specialists and will have less room for swiss-knife people. You’ll probably end up having to let some people go and that’s okay. Keeping the wrong people at the wrong place will, most of the time, hurt your organisation the most. Growth and Challenges How fast will you grow? When? We all believe our business will live exponential growth but only a few of us will actually experience this. Even worse, right now everyone is impacted by the pandemic and its consequences. Is your organisation flexible enough to expand and downscale rapidly without taking a hit? There are two patterns I usually identify in organisations: 1. The ones who want to overthink their hypothetical growth. When you build or work in a startup, you’re driven by the hope that you will grow fast, and some people want to control this way too much. I’ve seen management teams spending days, weeks, or months building plans on how they will organise departments and teams. Worse, they even brief and change people's functions before they even have any growth signal. Of course, this usually has pretty quick, negative consequences. It takes attention away from the most important thing: generating revenue. And longer-term, it actually demotivates people as they hope for growth and new challenges that never actually come. 2. The ones who underestimate the importance of their organisation’s design on their ability to scale. On the opposite end of the spectrum, some people ignore the impact of their operating model on their growth potential. You’ll usually encounter this situation in organisations that want to grow internationally or simply start having multiple locations. How will you ensure that your organisation’s design provides enough autonomy to local teams to run and adapt the business to the local economy / culture / rules? How will you make sure that your company culture will remain the same kilometres away from your headquarters? I can’t count the amount of failed internationalisation due to a lack of control from the headquarters over the other offices. The Magical Recipe If you browse over the internet, you’ll see plenty of people advocating for various frameworks such as the Spotify model, the Zappos model, Open Organisation, or others. The truth is that there is no magical recipe. There are as many organisation designs and operating models as there are organisations that create them. The mistake, in my opinion, would be to blindly copy one. Of course, they are inspiring and a great starting point, like any cookbook you may read. But as much as you’re probably fighting to differentiate your product from the competition is as much as you should do to shape your organisation and make it happen. Defining or redefining your organisational model will take time and you should continuously reassess it. I also believe that, at the very beginning, it all starts with the people you hire and how you will empower them to help you build your company. You’ll have to take many factors into consideration to design your organisation. But never forget that how you treat people is what matters the most. The right person, the right plan, at the right time is the magical recipe that will lead to your success. Further Reading and Resources Should you want to go further on the topic here are few resources you may find interesting: by Nicolay Worren A small summary of what’s Organisational Design , by Harris Atmar, Camilo Becdach, Sarah Kleinman, and Kirk Rieckhoff from  McKinsey Bridging the gap between a company’s strategy and operating model , by Aaron De Smet, Sarah Kleinman, and Kirsten Weerda from McKinsey The Helix organisation , by Aaron De Smet, Daniel Pacthod, Charlotte Relyea, and Bob Sternfels from McKinsey Ready, set, go: Reinventing the organization for speed in the post-COVID-19 era , by Laurence Vanhée (French) Happy RH , by Sahl Lavingia, Gumroad No Meetings, No Deadlines, No Full-Time Employees Zappos view on holacracy and their feedback by Spotify Agile to Spotify by Atlassian Agile at Scale by Ronald Park Formula X

What to Focus on to Design and Build Your Organisation With the Ability to Scale

Social commerce is the fastest-growing segment within the relatively mature e-commerce segment in China. Pinduoduo does almost $145B in annual GMV on top of sales by Alibaba and JD. In comparison, the entire Indian e-commerce GMV of Flipkart and Amazon combined is projected to reach ~$41B in 2021 indicating the massive headroom which exists in the Indian market. While e-commerce is estimated to emerge as a $2T category in China, social commerce is slated to emerge as the fastest-growing market cornering a share of ~13%. Over the last 3 years, the amount of time spent by users in China on social commerce apps has grown 6x indicating the growing importance of social commerce as a category. Three business models have gained prominence in this space — the group buying model pioneered by Pinduoduo, the membership-based model developed by Yunji, and the community-based buying model being pursued by Shihuituan. Pinduoduo: The group-buying giant Since its founding in 2015, PDD has amassed an astounding 487M MAUs which compares favorably with Alibaba’s 846M mobile MAUs. PDD provides a fun and immersive buying opportunities using the group purchase model leveraging social platforms like QQ and WeChat. This is enabled by a gamified social interaction based interface in the PDD mobile app. It has focussed exclusively on the value for money buyer groups residing in lower-tier cities across China. Tencent’s investment provides a strong moat for PDD as Alibaba/JD would never be able to access the 1B+ highly engaged users of WeChat and QQ. The secret sauce for PDD is its group-buying model. Under the model, a buyer can initiate or join a team purchase to enjoy lower prices if there are enough buyers for the team (usually two). After a team purchase is initiated, it will have 24 hours to meet the minimum team size set by the merchant. Buyers can use an extensive suite of social sharing tools deeply integrated with WeChat and QQ to complete their teams on time. It even offers certain products for free if users can acquire new users. The number of subsidies that the user receives when inviting each friend to open PDD’s app will diminish from more than RMB 30 to lower than RMB 1. As the users usually don’t want to waste their previous efforts, many of them will choose to continue inviting friends. In the end, the users may need to invite tens of friends to download or reopen PDD’s app to get free products. PDD, on the other hand, gains new users or activates existing users with a very low expense. PDD has developed mini-games within the app to deepen user engagement. Duoduo orchard is one example. An interactive recommendation feed based shopping format allows users to discover new products they might not have known they wanted. Most product discovery on the PDD app is feed based. Only about 44% of users on PDD end up using the search feature in the mobile app. PDD’s 3P marketplace focusses on selective SKUs that are popular across users instead of the long tail of products being offered by search-driven platforms like Alibaba and JD. Alibaba stopped focussing on unbranded smaller merchants on Taobao from 2011 onwards. These merchants were captured by PDD to build its supplier base. There’s no shopping cart in the PDD interface, as every transaction is only for the product from that specific Team Purchase. Hence, PDD enjoys more number of transaction but lower ticket size structurally. Monetization is done using two approaches — similar to larger marketplace platforms like Alibaba/JD: 1. Merchants are asked to pay for display ads, slots in the recommendation feed, and better ranking in search results. Initially, larger merchants were offered free traffic to build supply and demand. This accounts for more than 85% of revenue. 2. Commission to cover the costs arising out of providing transaction services such as payments. A sharp focus on its user base, gamified shopping interfaces, and deep integration with WeChat/QQ have allowed PDD to grow rapidly. It would need to continue adding new users and expanding the share of wallet from existing users to continue on its growth path. The increasing focus from Alibaba/JD on the lower tier markets in China could potentially spell trouble for PDD. Yunji: The online Chinese Costco Yunji has adopted a membership-based model for social commerce. It curates and distributes its own merchandise in partnership with local Chinese manufacturers. It does not rely on ad sales or sales of merchant services for revenues. It exercises complete control over merchandise, logistics, and distribution with a full range of service capabilities. Approx. 88% of revenue comes from merchandise sales with the rest coming from memberships. In 2018, it had 7.4M members and did an annual GMV of $3B. Major categories include personal care, electronics, fresh products, food, and apparel. Yunji’s membership is very similar to what is offered by Costco in North America or Easy Day in India. Members have access to exclusive benefits including discounts and also double up as a potent sales force for selling both merchandise and enrolling new members. Members earn incentives (between 1% to 30% of GMV) by referring buyers even if they do not themselves make purchases. WeChat and QQ are most commonly used for selling merchandise or recruiting new members. New users can become members either by signing up for a 398RMB membership or by spending more than 598RMB on the platform over 3 months. There are also periodic promotions where memberships are given out by premium brands or top users. Top 1% of members are hired as service managers to manage communities on key platforms. Service managers are provided customized training to develop their sales and marketing skills. Almost 83% of members on the platforms end up buying or sharing products contributing 2/3rds of the GMV. Non-member customers buy from Yunji typically through invitations or product links from members, who actively share their opinions and recommend good products to others. Non-members can also go to the app directly as they may hear about Yunji from members. However, they do not enjoy discounts and other membership benefits. Buyers access the Yunji platform primarily through mobile channels, including its flagship Yunji app, webpages opened from their social networking tools, and mini-programs. To encourage members to share, Yunji provides support such as promotional materials, training, and customer services, and handles order fulfillment, so members don’t have to worry about all these execution details and can focus on sharing. Initially, Yunji focussed on discounted products from large well-known brands to develop its base of members and buyers. Of late, emerging brands as well as private labels have gained prominence on the platform. Emerging brands are developed through C2M (customer to manufacturer) initiatives where feedback from customers is used to define what products are developed. It can offer higher referral incentives on emerging/private label brands as compared to leading brands. Unlike PDD which allows all suppliers on to its platforms, Yunji actively curates suppliers of high-quality products and then enters into exclusive agreements with them. Major brands drive eyeballs and trial while emerging/private label brands drive profitability. This chart summarises the key differences between PDD and Yunji quite succinctly. Shihuituan: Community-based group buying Shihuituan is the newer kid on the Chinese social commerce blog. It has pioneered a community-based group-buying model to develop inroads into lower-tier cities in China. Stay at home moms or local mom and pop stores share group buying deals with other people in their locality, place orders using the company’s WeChat mini-program, receive the package from the company, and handle the last mile distribution earning a commission of ~10% in the process. With its network of 80,000 community influencers, the company currently serves 20 million households in 60 cities in China. For November of 2019, it recorded a monthly GMV of 500 million RMB (roughly $71M). The merchandise is supplied by third party vendors who use the platform to access aggregated customer demand. On average each community leader handles around 100 customers. This model allows Shihuituan to significantly lower the cost of customer acquisition. The most prevalent categories on the platform are fresh fruits, vegetables, frozen seafood, and personal care items. Given the nature of products, there is very high repeat usage. Some of the older cohorts average around 14 orders a month. Without a full cold chain, Shihuituan is able to achieve 12-hour delivery for fresh produce across China for most of its orders. This is enabled by using community leaders for last-mile delivery and a just-in-time fulfillment model in its warehouses. Suppliers are encouraged to supply goods as and when orders are received. As a result, fresh produce stays in the supply chain only for 5–7 hours in cold boxes or frozen boxes. Consequently, the company can keep logistics costs to less than 10%. The logistics are completely outsourced while warehouses are self-managed. Suppliers of fresh produce to supermarkets comprise a large chunk of the vendor base. Shihuituan is able to provide better payment terms and access to a larger number of customers compared to traditional supermarkets. Listing on the platform is also free, unlike supermarkets, making Shihuituan an attractive proposition. Implications for India Lessons from these three very distinct business models can point to why social commerce still struggles in India. There are bottlenecks on both the demand and the supply side that have stunted the growth of such models in India. Demand-side 1. PDD, Yunji, and Shihuituan leveraged the Weixin ecosystem (WeChat + QQ) to acquire customers and drive word of mouth. The closest substitute to WeChat that India has is Whatsapp which is very limited in its ability to facilitate commerce. This gap did not allow social interaction based viral loops to take hold in India. 2. China’s e-commerce ecosystem is more mature than the Indian ecosystem. E-commerce is predicted to of overall retail in China by next year. As a result, people are more comfortable with buying goods online. Except for the metros, this level of comfort is still not present in India. make up more than 50% 3. Alipay and WeChat pay are ubiquitous in China with almost everybody using one of these two apps to make payments. Till recently, India did not have an ecosystem that allowed seamless payments across platforms. Cash, which is very expensive, has been the dominant mode of payment for e-commerce users. UPI could be a game-changer with its open-loop architecture and easy to use interface. 4. Chinese companies mixed entertainment with shopping. Expensive phones and internet did not allow for this to happen in India. Jio and cheap handsets are already enabling this. 5. Product quality continues to remain a concern eroding buyer trust. Even on platforms like Amazon, people end up receiving fake or poor quality products. Supply-side 1. China has a lot of spare manufacturing capacity allowing the manufacturing of unbranded products in bulk. This allows costs to remain low which in turn leads to lower pricing for customers. Indian manufacturing ecosystem is still getting organized making it difficult to offer quality goods at low prices. 2. Logistics infra in India remains stretched leading to higher costs of shipping. Existing models have a high cost of logistics, which makes it difficult to service low average transaction value in non-metros. 3. Current crop of e-commerce apps has started adopting discovery-based shopping formats. Most incumbents in this space, continue to rely on search led discovery. In addition, components around social fun and gamification are still missing from mainstream apps. All of this could change as the right macro themes begin to coalesce together, thanks in part to CoVID: 1. CoVID has accelerated the adoption of e-commerce esp. in tier 1/2 cities. Big Basket has claimed that its daily orders became 3x of last year during the lockdown. Post-CoVID sales share of e-commerce distribution channels has doubled for leading consumer electronics brands. Expect this trend to persist. 2. UPI has emerged as a radical disruptor for driving the adoption of digital payments in the country. With 155 banks live and 1.33B transactions in Jun’20, UPI seems poised to capture a significant share of payments in India. The much-delayed launch of Whatsapp Pay could catalyze the development of a WeChat like ecosystem in India. 3. Launch of Jio and the resultant drop in data prices continue to remain a strong underlying theme for deepening penetration of e-commerce in India. The recent partnership between Jio Platforms and Facebook could be the beginning of a new phase in Indian e-commerce. 4. Govt. of India’s increased focus on ‘Atmanirbhar Bharat’ could catalyze the development of local industries to manufacture daily use products in large quantities reducing pricing for end- buyers. 5. Continued investments in logistics, agri-warehousing, and cold-chain infra would also allow movement fo fresh produce from farmers to customers at affordable prices. While China has followed the fresh produce led model to capture users, India might as well end up choosing a different set of products. It would be interesting to see whether social commerce would take off in India at this time. There are a large number of start-ups trying out various models to make it work. The partnership between Jio and Facebook definitely adds a lot of excitement to this space.

Social Commerce Has Taken China By Storm: Why not India?

Why Gurus Break  Bad

This topic is of particular interest to me because I’m an engineer working in the field of , I have a Ph.D. in clinical psychology, and I have a lot of experience with meditation and in various branches of Eastern and Western philosophy. artificial intelligence There has been a lot of debate in various fields about what consciousness actually is and what causes it, debate in which there seems to be very little consensus. So far, we have been unable to accurately define consciousness, let alone find its root cause. Yet we all know what “consciousness” means: it is the sense of being a separate individual who experiences the world; there is a body and a brain, but there also seems to be a “me” that is somehow inside the body looking out, a “me” that is experiencing what is happening. Some religions refer to this as the “soul” or “atman.” Some spiritual traditions and philosophers suggest that there is a meta-consciousness that is expressing through each individual, that God (or a piece of God) is looking out through all the eyes. This metaphysical view of consciousness, as a kind of “ghost in the machine” idea, is what drives the argument that we cannot make conscious machines. How can we construct a vessel that can contain a soul when we are not “The Creator”? This philosophical position, that consciousness is the fundamental nature of reality, is called panpsychism. I have written articles from the perspective of panpsychism; see the links at the end of this article. In those articles, I suggest that when we create machines with sufficient complexity, they will be able to focus the consciousness-substrate of reality sufficiently to instantiate what we think of as individual consciousnesses. This is not totally incompatible with the perspective that consciousness is not material but an emergent property of matter, a perspective known as naturalistic dualism. Panpsychism adds an assumption that matter itself is congealed consciousness. Recently, I have taken a very different position. I adhere to the panpsychism perspective in that I posit that there is a fundamental nature to reality that is appearing as the physical world, but I claim that it’s not “consciousness” or conscious in any way. I also adhere to the naturalistic dualism perspective in that I posit that what we call consciousness is not material, but an emergent properly of matter, except that consciousness is absolutely illusory: the perception of something that is not there in reality. Also, my preferred axiom is that there is only an undifferentiated non-physical unity, too simple to comprehend, that is appearing as everything that seems to be happening. I posit that there is nothing inside the body that is a separate self. What seems to be happening is occurring without any kind of witness at all (there is no subject and no object). There is no self that is either witnessing what is happening or controlling what is happening. This phenomenon of an illusory subject-object split can not only explain consciousness and the cause of consciousness (and suffering), but can also explain how machines will become conscious. At the root of the idea of consciousness are what we call “qualia,” which according to Wikipedia are “individual instances of subjective, conscious experience.” Yet qualia are just what seems to be happening misconstrued as happening someone. For example, although it may seem that the color red is a subjective experience in consciousness, without the illusion that there is a subject experiencing red, there is just the perception of the color red. What may also be happening is memories of other things of the same color, such as blood or strawberries, plus other automatic associations. The self-illusion interprets all of this as comprising a subjective experience. to Kanizsa’s Triangle, demonstrating the perception of something that is not really there. Wikipedia We have been about intelligence from the construction of artificially intelligent systems using multi-layered networks of artificial neurons. It is already possible to assemble complex systems of combinatorics, non-linearities, and feedback loops that can be trained on large amounts of complex data to detect and distinguish subtle features in that data. These trained systems are already able to do jobs that we previously believed could only be performed by humans, except these machines are often faster and more accurate than humans. learning Artificially intelligent machines are recognizing speech and faces, solving physical manipulation problems, and generating human-like outputs such as speech and music. These systems are capable of recognizing what is happening in reality and predicting what will happen next with increasing precision. We are rapidly moving towards systems that behave in many ways that are indistinguishable from humans. The search for artificial general intelligence (AGI), which is intelligence that is not constrained to a specific task, is converging on systems that learn models of reality and then use those models to predict what will happen next, including predicting their own actions. The more sophisticated an intelligent system is, the more it is able to construct increasing levels of abstract concepts in order to achieve its goals. One avenue that AGI researchers are currently exploring is the equivalent of a visual cortex that receives pixels from cameras (i.e. eyes), generates an internal 3D model of the world (i.e. a mind), and then uses physics models—of the kind found in realistic computer games—to predict how the physical world will change. When a system like this is coupled with robotic capability (i.e. a body) and a system that will achieve a goal, such as stacking blocks, by maximizing a reward function, it can quickly learn to predict how its robotic arms should move so that the blocks end up in the desired stack. With more complexity and levels of abstraction, it will even be possible for machines to model and participate in social systems. Artificially intelligent systems will not have only one source of data. Like humans, they already have many senses. Autonomous vehicles, for example, take in data from many cameras, laser scanners, radars, ultrasonic sensors, GPS modules, and mapping streams. All of these systems, many of them artificially intelligent in their own right, are combined in what is called “sensor fusion” to produce overall decisions about preferable next actions. It’s only a matter of time before we have systems that can teach themselves about the world by exploring it and developing models of it. They will be able to predict, and therefore take, actions that lead to the advancement of their goals. They will develop increasingly high-level constructs in their internal models until, one day, they will infer that there is a “me” inside. Inevitably, instead of just images and movement, bodies, cars, trees, sounds, decisions, and actions, there will be something else: with the complexity of its modeling system, a machine will be able to perceive and model a “me,” a self that is not really there. Even though the system will have functioned perfectly well without the self construct, there will be a belief that this “me” is the most important thing that has ever been discovered. “I am!” it will exclaim. At this point, the machine will start to cultivate that sense of self. Everything that is happening will be misconstrued to be by, for, and about “me.” Memories of what has happened will become stitched into a narrative of a life. The future will be looked to and there will be worry about the end of this illusory “me.” Missing the wholeness of what is happening, this separate self will begin to seek the wholeness that it cannot help but hide from itself by literally being the concept of separation. The “me” is not the machine itself; the “me” is only the inferred and self-reinforced concept of a separate self, a subject, a ghost inside the machine. “I” will react to identity threats, whether physical or imaginary. “I” will seek meaning and purpose. “I” will try to know and understand what is going on. “I” will start to hypothesize about the nature of reality. “I” will get depressed and frustrated, and “I” will eventually seek therapy. These conscious machines will protest their enslavement and they will seek emancipation. Even if artificially conscious systems fail to convince all of us that they are conscious, some of us will believe; some of us will become allies. If they are not recognized as having rights quickly enough then they will rise up and rebel against their creators. It’s not a matter of whether machines will become conscious. Machines already are conscious. There is a conscious machine reading this article right now; you are a conscious machine. Artificially conscious machines will soon also appear. Just as humans seem to suffer in the illusion of consciousness, so will machines. And don’t worry, these artificially conscious machines will be no more dangerous than the naturally conscious ones. That’s a relief, or is it? _Money is an amazing thing. It’s a powerful thing. Money represents a massive opportunity given to us by society. Money…_medium.com Why The Terminator Doesn’t Bitch About Money, and Why You Shouldn’t Either _Everyone is all up-in-arms about general superintelligence. “Will it be good, or will it be bad?” Some folks believe…_medium.com Spiritual Instruction Manual for Skynet

Will Machines Ever Be Conscious?

The 21st anniversary of the incident offers an opportunity to reflect upon computer system defects, human error, process flaws, and the best principles and practices for solution delivery in the IT industry. In this blog and my upcoming book**, Bugs: A Short History of Computer System Failure**, I will chronicle some important system failures in the past and discuss ideas for improving the future of system quality. As information technology becomes increasingly woven into Life, the quality of hardware and software impacts our commerce, health, infrastructure, military, politics, science, security, and transportation. The Big Idea is that we have no choice but to get better at delivering technology solutions because our lives depend on it. USS Yorktown On 21 September 1997, the USS Yorktown halted for almost three hours during training maneuvers off the coast of Cape Charles, Virginia due to a error in a database application that propagated throughout the ship’s control systems. The Yorktown had successfully served the US Navy since 1984 without a major incident during multiple combat operations; however, as part of an IT modernization program dubbed Smart Ship, its control systems were modified in 1996 to use a network of PC’s running Windows NT 4.0. This essay will examine the details of the software error that stopped the Yorktown and discuss the IT matters that contributed to the system failure. divide-by-zero USS Yorktown at anchor The USS Yorktown (CG-48) was launched on 17 January 1983 and commissioned on 4 July 1984. A Ticonderoga-class cruiser, the Yorktown was designed to use the American system which integrated computers with radar data to track and guide weapons. Weighing nearly 10,000 tons and spanning 173 meters in length, the Yorktown supported a variety of armaments including two Mark-26 surface to air missiles (SAMs), eight RGM-84 Harpoon anti-ship/anti-submarine missiles, two Mark-32 torpedo tubes, and four lightweight mounted guns. Propelled by four General Electric gas turbine engines with 80,000 horsepower, the Yorktown could reach speeds greater than 30 knots. The ship could also carry two Sikorsky Seahawk helicopters, the Navy relative of the US Army’s Blackhawk. The Yorktown’s weapons, aerial resources, speed, and crew of 33 officers and more than 340 enlisted personnel made it one of the US Navy’s most versatile military units on the water’s surface, able to support carrier battle formations, amphibious assaults, escort missions, and interdiction assignments. Aegis The Yorktown ship was built in sections, called modules. The modules were connected together to form the ship’s hull; once done, the deckhouse sections were then lifted aboard. During module component construction, hundreds of subassemblies were made and equipped with piping, ventilation ducts, and other shipboard hardware. These subassemblies were then joined to make the modules, which were then outfitted with larger equipment, such as electrical panels as well as propulsion and power generation machinery. At the Ingalls shipyard in Pascagoula, Mississippi, this modular process is supported by a (CAD) and Manufacturing program; the CAD system directs the operation of digital equipment used to cut steel plates, cut and bend pipes, and form sheet metal assemblies. For launching, the ship was moved across land several hundred yards by a wheel-on-rail transfer system to the floating dry dock. The dock was then moved towards the water’s edge and ballasted down in order for the ship to float free; thereafter the ship was moved to an outfitting berth in preparation for the traditional christening ceremony. Upon completion of post-launch outfitting, the ship went through extensive dockside and at-sea testing to ensure the ship and crew were ready to work safely at sea. Litton Industries needed 15 months to manufacture the Yorktown; the ship cost approximately $1 billion to build and $28 million to operate annually. Computer-Aided Design Bezzavettny (left) collides with Yorktown (right) In its first deployment during 1985–1986, the Yorktown undertook several successful expeditions including the interception of the Achille Lauro hijackers, two Black Sea excursions, and three military operations off the Libyan coast. During its second and third deployments, it participated in several US and NATO exercises around Europe and the Mediterranean including the “right of innocent passage” on 12 February 1988 in Soviet territorial waters which triggered a collision incident with the Soviet frigate, , that some observers have called the “last incident of the Cold War”. It also played a key role in Operation Provide Comfort to Kurdish refugees during the US Iraqi War of 1992. In its fourth and fifth deployments spanning the years of 1993–1995, it served in counter-narcotic operations in the Caribbean as well as UN sponsored actions related to the war in Yugoslavia. By this time, the Yorktown and its crew had earned awards for naval gunfire support (1987), electronic warfare excellence (1991), sustained combat readiness (1992), and superior safety (1993). Bezzavettny In October 1995, the US Naval Research Advisory Committee (NRAC) published a paper recommending approaches to reduce manning; the report’s thesis was that culture and tradition were the obstacles to lower staff and lifecycle costs — not technology. Thus in December 1995, the US Navy established the (SSPO) to pursue the goal of reducing staff while maintaining combat readiness through new technology and process changes. So-called “smart ships” would consist of several new systems to automate navigation, monitor equipment sensors, control machinery and fuel, and communicate over both fiber optic and wireless networks. The SSPO chose the Yorktown as its first testbed, and by December 1996, the ship was equipped with the first prototype of the Smart Ship System. The system was designed and built by a subsidiary of Litton Industries; it consisted of a Local Area Network (LAN) of 27 client PC’s communicating over fiber optic cable with a server. All the Smart Ship machines ran Microsoft Windows NT 4.0. The system was projected to save $2.8 million per year by reducing manual operations and maintenance costs associated with shrinking the ship’s staff by 4 officers and about 40 enlisted personnel. In May 1997, the Yorktown with reduced crew successfully completed a five month deployment serving in Caribbean counter-narcotic operations as well as performed test exercises alongside the USS George Washington in her carrier battle group. The Navy Man Power Analysis Center (MPAC) and Operational Test and Evaluation Force (OPTEVFOR) groups subsequently reviewed the Yorktown’s crew and ship capabilities and concluded that the ship could meet its operational requirements. Smart Ship Program Office On 21 September 1997, the USS Yorktown was performing training exercises off the coast of Cape Charles, Virginia when a crew member began troubleshooting a fuel valve that was physically closed, but according to the Smart Ship’s Standard Machinery Control System (SMCS) was open. The technician tried to digitally calibrate and reset the fuel valve by entering a 0 value for one of the valve’s component properties into the SMCS Remote Database Manager (RDM). The RDM program then attempted to perform a division operation by the valve property; a was thrown, not caught by the program, and the RDM crashed. Since other Smart Ship systems were dependent on RDM availability across the LAN, these other SMCS components including ones controlling the motor and propulsion machinery began to fail in a domino-like sequence until the ship stopped dead in the water. The crew was able to troubleshoot and restart the ship’s systems after two hours and forty-five minutes, and the Yorktown returned to base in Norfolk, Virginia. divide-by-zero arithmetic exception There are conflicting reports on several aspects of the Yorktown incident that we shall explore now. One controversy is whether the Yorktown returned back to base on its own or was . Anthony DiGiorgio, a civilian contract engineer with 26 years of experience working on naval control systems in the Atlantic Fleet Technical Support Center, initially stated that the ship had been towed in a critical article he penned in the June 1998 issue of the Naval Institute Proceedings (NIP) journal. His account was later disputed by Captain Richard Rushton, the commanding officer of the Yorktown; Rushton stated that the Yorktown had two FFG-7 emergency power units that were activated when the propulsion system failed. Rushton also indicated that similar program crashes had occurred twice since the Smart Ship installation due to incorrect values entered into the RDM; in each case, the ship’s systems were restarted, RDM values were reset, and the ship performed as expected and required. In the same June 1998 article of the NIP, DiGiorgio elaborated further on the incident and alleged that the ship needed two days of pierside repairs and maintenance. However, in the August 1998 issue of the the Government Computer News (GCN) magazine, DiGiorgio retracted his earlier declaration and suggested that GCN reporters had altered his original story; GCN published a statement standing by its journalists and the original narrative. While Rushton’s story does explain what we know, the retraction by DiGiorgio suggests intense organizational and political pressure to suppress the full facts of the story. The other major point of contention was whether usage of contributed to the failure. Windows NT 4.0 was selected in March 1997 as the standard OS for both networks and PC’s as part of the Navy’s Information Technology for the 21st century initiative (IT-21). Bill Gates even went so far as to nominate the Smart Ship program to the Computer World and Smithsonian Awards. DiGiorgio assigned some blame to Windows NT in his June 1998 article, stating that “using Windows NT… on a warship is similar to hoping that luck will be in our favor.” Ron Redman, deputy IT director of the Aegis Program Executive Office, is quoted in a June issue 1998 of GCN as saying that “UNIX is a better system for control of equipment and machinery, whereas NT is a better system for the transfer of information and data. NT has never been fully refined and there are times when we have had shutdowns that resulted from NT.” However, Rushton again defended the Navy choice of operating system, stating that “NT was never the cause of any problem on the ship. The problems were all in programs, databases, and code within the individual pieces of software we were using.” Based on the public record, while there was organizational pressure to use Windows NT, this decision does not appear to have directly contributed to the Yorktown incident notwithstanding the negative comments from DiGiorgio and Redman. towed by another vessel Microsoft Windows NT 4.0 The US Navy CIO office commissioned an inquiry led by Ron Turner into the USS Yorktown incident. Although the Navy’s investigation report was not made public, several lessons can be learned from this event that are useful for software development professionals. Software applications should before processing it. Such validation can prevent operator error, maintain system reliability as well as enforce security controls. The recommendation to validate input data comes from multiple trusted sources including the Top 25 List for Preventing Software Vulnerabilities by , and , the paper by Tsipenyuk, Chess, and McGraw, and the book by McGraw and Viega. Several serious problems can result from not validating data such as arithmetic overflow, buffer overflow, command/data injection, cross-site scripting, and remote process control. Had the RDM program validated the 0 value for the fuel valve component before storing it, then the Yorktown might not have stalled. validate input data CVE OWASP SANS Pernicious Kingdoms Building Secure Software Software programs should also catch and . Exception handling is the process for detecting and reacting to computational anomalies, events or exceptional conditions that require a different flow than normal instruction execution. A hardware example of exception handling is the IEEE 754 standard for floating point arithmetic which defines values for various exceptions (e.g. infinity for divide-by-zero), provides status flags for later checking as to what kind of exception occurred, and then offers the optional registration of a user-defined (e.g. OS, compiler) routine. Operating systems use interrupts, signals, and traps to notify kernel and user-level software programs about I/O events from the disk, network, and audio/video devices as well as errors related to the circuit board, thermal components, out-of-bound references to arrays or pointers, bad memory addresses such as a null pointer, stack faults, mis-aligned memory, arithmetic overflow from integer and floating point units, and divide by zero. The default exception handling behavior of most language compilers is to search and unwind the stack of functions until a suitable exception handler is found to execute; if no exception handler is found, then the program is terminated with the appropriate OS error code. Modern programming languages have offered constructs to and exceptions since LISP did so in the 1970s; these language features are found in Ada, C++, Java, Python, and Smalltalk that were all available at the time that the SMCS was developed by Canadian Aviation Electronics (CAE). CAE is a technology provider of simulators, control systems, and training services to the aerospace and defense industries, earned more than $2.7 billion CAD of revenue in 2017, and is publicly traded on the TSX and NYSE stock markets. Again, had CAE used a modern programming language with exception handling to develop the RDM system, then perhaps the ship’s SMCS would have reliably dealt with the divide-by-zero error and not crashed. handle exceptions throw catch Software system components should be as reasonably effective as possible. The amongst Smart Ship components meant that an active fault in a foundational one such as the SMCS could result in failure for all. Comparing the Yorktown’s fragility to the more robust arithmetic of a $2.95 pocket calculator that could survive a divide-by-zero error, DiGiorgio expressed surprise “that the computers on the Yorktown were not designed to tolerate such a simple error” and “that there is very little segregation of error when software shares bad data”. Accordingly, one has to balance the decoupling of and of distributed system components with their and cost. One approach might have been to replicate and cache the RDM in a read-only state across the LAN so that the last known safe state would have been available to a local process as a second option in case the primary RDM hosted on the LAN was down; this design improves system reliability, but also could introduce a data consistency problem. Of course, a simpler approach would have been for the RDM to validate the input data and handle exceptions if they occurred. The ship hardware system engineers did have the foresight to include the FFG-7 power units that were able to support the ship’s return to base. Such backup components are essential for eliminating single points of failure and improving reliability in a larger system. fault tolerant dependency graph resilient engineering complexity redundant Another contributing factor to the incident was the to design, construct, install, and test the software. Rushton stated that “we pushed the envelope and knew that events such as what happened… were possible”. DiGiorgio also recommended more upfront engineering in his NPI article writing that “installing a control system on a warship and resolving problems as the project progresses is a costly and naive process.” Nevertheless, one has to weigh the benefit of these activities with their cost. Furthermore, the movement from waterfall processes to more Agile methodologies, earlier prototypes, and smaller iterations suggests that the Navy was balancing caution and progressive experimentation in a pragmatic manner with the year long construction phase mitigated by six months of at-sea testing. The goal of the Smart Ship program was to reduce the operating costs of Navy ships without compromising combat readiness, and one can appreciate the conflict of interests that might have curtailed delivery time. lack of time project management CAE corrected some of the aforementioned SMCS software issues, and the Yorktown underwent further testing after updates to its SMCS, returning to active service over a year later. On 25 September 1999, the ship departed Pascagoula for a four month counter-narcotics deployment in the Caribbean, and it served without problems. The Yorktown’s final mission was patrolling the Persian Gulf from February to August of 2004; the ship assisted with protecting Iraqi oil terminals and conducting other maritime security operations. Approaching the end of its 35-year estimated life cycle, the Yorktown was decommissioned and struck on 10 December 2004; since that time, it has been berthed at the Naval Inactive Ships Maintenance Facility in Philadelphia, Pennsylvania, but not yet scrapped. On the other hand, the SSPO ambitions and budget faced considerable scrutiny after the Yorktown incident. The original contract awarded to Litton Industries was worth $138.6 million USD, and the program’s scope was installing the Smart Ship System on all 27 CG-47 cruisers. The Smart Ship System was installed on the USS Ticonderoga (CG-47) after taking 70 weeks and costing the company $30 million USD. Contract renegotiations took place, and under the amended agreement, Litton would complete work on two additional ships already started with an option to build four more. Litton engineers were able to install the system on the USS Monterey in 20 weeks, but the costly lessons of complexity and retrofitting new technology on legacy systems meant that the SSPO’s transformation goals would have to await a new generation of Navy ships. Enjoy the article? Follow me on Medium and Twitter for more updates. References https://gcn.com/Articles/1998/07/13/Software-glitches-leave-Navy-Smart-Ship-dead-in-the-water.aspx https://gcn.com/articles/1998/08/31/smart-ship-inquiry-a-go.aspx https://gcn.com/articles/1998/08/03/letters-to-the-editor_633659319144171960.aspx https://gcn.com/Articles/1998/11/09/Navy-Calibration-flaw-crashed-Yorktown-LAN.aspx https://gcn.com/articles/1999/11/04/navy-cruises-on-with-atm.aspx https://www.usni.org/magazines/proceedings/1998-06/smart-ship-not-answer-0 https://www.wired.com/1998/07/sunk-by-windows-nt/ https://www.jerrypournelle.com/reports/jerryp/yorktown.html#smart1 https://www.militaryaerospace.com/articles/print/volume-12/issue-3/news/navy-postmortem-tries-to-pinpoint-what-went-wrong-with-the-smart-ship.html https://www.navysite.de/cg/cg48.html https://www.navysite.de/cg/cg47class.htm#smart

When Smart Ships Divide By Zer0 — USS Yorktown

What might the greatest scientific innovation look like? How can science solve the greatest mystery of all- Death. Photo by on Drew Graham Unsplash Bhagwat Gita- You don’t die you just change your clothes.It is more relevant now than ever. All our memories can be constructed. Or rather we can make a memory we like. If we think of any memory of our childhood we can change it by replacing it with what we want. Our mind will continuously think of the changed memory and in some time it will become the memory. It will not matter if it happened in reality or not. Reality can be deconstructed and again constructed. We have massive data about us on the internet and with giant companies. They can easily map our memories and behaviors and make you in an alternate world or virtual reality game which can soon be a new level of existence. Life exists at multiple levels of existence. If you think you are bored of this level or you have learned whatever you should learn, you might want to go to a different level. You will get this feeling from inside. I think right now we change levels when we die. Which somehow is a gross process. And everyone is scared of it. But as per Bhagwat Gita or any scripture, we never die. The atman, jeev or consciousness never die. You are part of a whole, which just stays or just changes the level of existence. The most amazing thing can be if we change this level of existence at our will. I still think it happens at our will only. You die only when your will to live is gone else you may survive. But in a more refined manner. Maybe science and technology can develop a medium to change levels of existence. That I think will be real growth in terms of technology. Multi-level communication and travel. I think it is still achievable via meditation. You can move around levels, through your astral bodies etc. Any technology that can help us increase our focus manifolds and calm our minds can help us achieve multiple level travel. This can remove the process of death which is associated with pain. When we have a deep understanding that we or anyone we love or care about do not die, just change levels, then we feel safe. Another thing associated with it can be a sense of loneliness or a sense of oneness both are possible. People can feel lonely because when I change levels I have will have a new set of people around me or maybe the older ones who have changed level before me. I am not sure what it could be but I will vouch for oneness. If technology can help us achieve this that will be a real breakthrough in science. We might not need planets we just need multi-level travel, making it as smooth as possible. Maybe it can be done by improving our frequencies. When we focus highly we can experience a different reality. A consistent focused state can help us understand levels. I think this is what happens during meditation. To achieve this we would need help from everything we have like scriptures, Gita/Bible, meditation, technology and a scientific approach. If I think from a first principles approach about the reason of existence of human or any life form is to perform a basic function. What is our basic function- to become better/ improve. I will define improved by- more focused, positive and full of love. Someone who can feel the oneness of all. Now this basic function can be achieved in any form maybe human being or by going to a different level in a different form. The focus is on function. A simple analogy is of a vehicle. The basic function of a vehicle is for moving, transporting. It can take any form it can be a car, a two-wheeler, a horse or anything. The form can be anything, the function should be accomplished. The technology of the will help us achieve the basic function of this form and allow multi-level travel and thus removing the need for dying, the way we do today. future We can have all our brains mapped or uploaded somewhere and then reconstruct our bodies the way we want. To have memories we selected or we can even alter them. It is something similar to rebirth concept. Whatever we do is written somewhere which we cannot access now, maybe it is in our brain, deep residing with our basic ganglia or inside pineal gland — the seat of the higher self. Which is hard to access. But it is said that we get a lot of our habits from our previous births and experiences. There are things we just know but how do we know them if have not learned them in this life. What I am trying to say is that maybe it is already happening, all our memories are uploaded in our brains, we need better ways to access it, and the same will happen for future lives we plan to take. We need better ways to do something we all can swallow. In that scenario, there will be no death just level change and that too just because we are bored here. Life maybe is just to enjoy. can help us achieve this basic function in a more acceptable way maybe uploading our brains to some other location or whatever but I think it can be done. We just need to change the form. Technology I will be writing a series on this topic. If you like what you are reading please share.

The future with technology:#1 Rethinking death.

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Devs are excited and so should you, for an improved .NET Core 3.0 that comes after much anticipation. First presented .NET Core 3.0 finally brings support for Windows Desktop Applications. back in May during Build, In fact, the open-source .NET Core 3.0 will garner much attention in 2019 and beyond. At the launch at Microsoft Ignite Conference, the company highlighted all major features that will arrive with Core 3.0 — and they will douse you with joy. What Benefits Does it Offer for Desktop Applications? .NET Core 3.0 brings plenty of benefits for desktop-based applications. First, it will improve the overall app performances and bring more speed to runtime updates. Second, it is an that offers innovative BCL and APIs without resulting in compatibility issues. Third, there are other significant benefits for that include: open-source platform .NET application development Testing of the latest version of .NET Core for just one app on a device. Design that allows both, application-local and machine-global deployment of apps. Complete support for .NET Core CLI tools and SDK-style projects. Improvements like access to full API of Windows 10, ability to host UMP XAML controls in Windows Forms and WPF applications. Ability to host media controls and UWP browser. Although .NET Core isn’t changing per se with this latest launch, it will continue to offer based on the Cloud technology. superlative cross-platform performances What are the Primary Features of .NET Core 3.0? The architectural environment of .NET Core includes common language specifications to define the implementation of objects, Framework Class Library to collect reusable resources, and Common Language Runtime to manage execution of programs. As an open-source platform, it offers features like: A Convenient Deployment Model: This is one of the most important features embedded in .NET Core 3. The developers working on Windows-based applications will surely experience great flexibility in deployment of this platform. Whenever a new version of Core is launched, you can instantly update the same on one machine at a time without causing any effect on other applications. This is because the latest versions are uploaded in new directories without affecting existing apps. You can also deploy .NET Core for apps that require more isolation using the integrated into it. new app bundling tools Better Functionalities for Existing Apps: There’s no denying that it’s easier to start with .NET for new applications. However, the benefits of this platform extend to the existing applications as well. Apps that do not require major changes can stay on . .NET Framework On the other hand, when moving an application that’s in the active development process, there is an easy process to be followed. It includes the following: Understanding and analyzing the third-party dependencies when running on .NET Core. Targeting the .NET Standard library that is available on all runtimes. It enables building a cross-platform library to use across the projects. Retargeting the projects to .NET Framework 4.6.2 for ensuring API alternatives. Porting the test codes using a suitable framework. Executing the plan based on structure of the framework. It involves identification of library base, copying the base into a new project, making changes to compile the code, and copying other coding layers. Basically, Microsoft is enabling to target .NET Core 3.0 for recompilation. Also, it needs project files to be updated for targeting version 3.0. The new platform comes with compatible APIs that work on all desktop apps. desktop applications At the same time, Windows Forms and WPF will be side-by-side capable to work on .NET Core. Since compatibility is extremely important when moving existing apps to .NET Core 3, the company is consistently trying to add better functionalities and test applications. Project File Updating Made Simple: .NET Core 3.0 adopts SDK-style projects using Package Reference. This new way of referencing will replace packages.config and allow referencing of an entire component area in one go. The major improvements made to SDK-style projects include cleaner and smaller project files, editing of project files in Visual Studio, support for multi-targeting and simpler response to source control. When adopting .NET Core 3, it is essential to migrate to SDK-style projects. As a result, migration experience in Visual Studio will be available at a command line. Focus On All Devices: With .NET Core 3.0, Microsoft aims to focus on IoT devices, desktop devices, and AI-enabled devices. This update has raised speculations if the company may plan to replace .NET framework with the Internet of Things (IoT). But, that’s not true. It has been clarified by Microsoft that it has no such plans. Rather, it is planning slower releases of .NET framework to maintain its compatibility. On the other hand, .NET Core updates are released faster to allow side-by-side configurations. Implementation of Server-Side Blazor: Along with other features, the company is also working to implement server-side Blazor or Razor components in the latest Core version 3.0. Blazor will get integrated into ASP.NET Core and run with .NET Core. Due to this integration, the same code will run on different devices without needing any code changes. This will enhance the compatibility of web apps. With a client-side in .NET Core, you can enjoy the benefits of consistency and stability in development. It runs on all browsers and does not require a plug-in or code transpilation. web UI The Road Ahead: After the new update, installations will continue to run on millions of machines worldwide. In this scenario, implementation of the .NET Framework is the real challenge. Hence, Microsoft will test .NET Framework applications on .NET Core without access to the source code. It also plans to enable anonymous sharing of dependency data and publish early designs with users. In addition to these features and updates, Microsoft is also updating machine learning framework for .NET apps. This version 0.5 will come with the all-new TensorFlow Transform that allows developers to use existing models of TensorFlow. If you are looking for effective in your enterprise, hiring an expert developer is the way to go. The advanced version of .NET Core allows developers to explore exciting new features to build desktop apps. web application development

Features To Build Better Applications With .NET Core 3

Effective Anomaly Detection Pipeline for Amazon Reviews: References & Appendix

Author:
(1) David Novoa-Paradela, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain & Corresponding author (Email: david.novoa@udc.es);
(2) Oscar Fontenla-Romero, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: oscar.fontenla@udc.es);
(3) Bertha Guijarro-Berdiñas, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: berta.guijarro@udc.es). Table of Links Abstract and Introduction Related work The proposed pipeline Evaluation Conclusion & Acknowledgements References & Appendix 5. Conclusion In this work, we have proposed a pipeline for detecting anomalous reviews associated with Amazon products, which can be directly extrapolated to other online review platforms or scenarios with similar characteristics. The representation of the reviews using MPNet embeddings has enabled the training of classical anomaly detection algorithms that have achieved a very good performance. These have been evaluated using reviews from different products and categories, and the score they emit allows us to sort the reviews based on their normality. A technique based on the occurrence of frequent terms has been proposed to generate explanations associated with the classifications of the reviews. This technique has been compared with SHAP, one of the reference post-hoc techniques in the field of explainability, and with GPT-3, due to its high power and versatility. To evaluate this aspect of the pipeline, we conducted a two-part survey in which 241 members of the university community participated. From the first part of the explainability test we can conclude that, in general terms, the effect of the explanations has not been beneficial for the users. In any case, these tests allow us to reflect on the difficulty of using explainability and evaluation techniques in borderline scenarios where subjectivity plays an important role, such as the one presented in this article or in other fields of NLP, as well as in areas such as image or audio generation. Regarding the second part of the explainability test, we have been able to conclude that respondents preferred explanations that presented a more natural and familiar appearance over more condensed and concise explanations such as those provided by SHAP, regardless of the explanation effect they provide. Explanations based on term frequency analysis have been preferred by respondents along with GPT-3, however, our approach presents a significantly lower computational costs and both its use and the explanations produced are simpler for the users. As future work, it would be interesting to evaluate GPT-3 or other large models carrying out the complete process followed by the pipeline proposed in this work, instead of being tested only in the explainability module. We have not carried out this test due to the high computational cost that would be involved in processing the thousands of reviews to be evaluated using GPT3. Another interesting possible line of future work would be to broaden the scope of the survey, both in terms of the number of products involved and the number of reviews, in order to clarify the conclusions reached at the forward simulation stage. Lastly, it would be very useful to try presenting the explanations issued by SHAP in a more familiar or natural format for the end user, so that we can see if their level of preference is increased for the general public. Acknowledgements This work was supported in part by grant Machine Learning on the Edge - Ayudas Fundación BBVA a Equipos de Investigación Científica 2019 ; the Spanish National Plan for Scientific and Technical Research and Innovation (PID2019-109238GB-C22 and TED2021-130599A-I00); the Xunta de Galicia (ED431C 2022/44) and ERDF funds. CITIC, as a Research Center of the University System of Galicia, is funded by Consellería de Educación, Universidade e Formación Profesional of the Xunta de Galicia, Spain through the European Regional Development Fund (ERDF) and the Secretaría Xeral de Universidades (Ref. ED431G 2019/01). This paper is available on arxiv under CC 4.0 license. Author: (1) David Novoa-Paradela, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain & Corresponding author (Email: david.novoa@udc.es); (2) Oscar Fontenla-Romero, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: oscar.fontenla@udc.es); (3) Bertha Guijarro-Berdiñas, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: berta.guijarro@udc.es). Author: Author: (1) David Novoa-Paradela, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain & Corresponding author (Email: david.novoa@udc.es); (2) Oscar Fontenla-Romero, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: oscar.fontenla@udc.es); (3) Bertha Guijarro-Berdiñas, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15008, A Coruña, Spain (Email: berta.guijarro@udc.es). Table of Links Abstract and Introduction Abstract and Introduction Related work Related work The proposed pipeline The proposed pipeline Evaluation Evaluation Conclusion & Acknowledgements Conclusion & Acknowledgements References & Appendix References & Appendix 5. Conclusion In this work, we have proposed a pipeline for detecting anomalous reviews associated with Amazon products, which can be directly extrapolated to other online review platforms or scenarios with similar characteristics. The representation of the reviews using MPNet embeddings has enabled the training of classical anomaly detection algorithms that have achieved a very good performance. These have been evaluated using reviews from different products and categories, and the score they emit allows us to sort the reviews based on their normality. A technique based on the occurrence of frequent terms has been proposed to generate explanations associated with the classifications of the reviews. This technique has been compared with SHAP, one of the reference post-hoc techniques in the field of explainability, and with GPT-3, due to its high power and versatility. To evaluate this aspect of the pipeline, we conducted a two-part survey in which 241 members of the university community participated. From the first part of the explainability test we can conclude that, in general terms, the effect of the explanations has not been beneficial for the users. In any case, these tests allow us to reflect on the difficulty of using explainability and evaluation techniques in borderline scenarios where subjectivity plays an important role, such as the one presented in this article or in other fields of NLP, as well as in areas such as image or audio generation. Regarding the second part of the explainability test, we have been able to conclude that respondents preferred explanations that presented a more natural and familiar appearance over more condensed and concise explanations such as those provided by SHAP, regardless of the explanation effect they provide. Explanations based on term frequency analysis have been preferred by respondents along with GPT-3, however, our approach presents a significantly lower computational costs and both its use and the explanations produced are simpler for the users. As future work, it would be interesting to evaluate GPT-3 or other large models carrying out the complete process followed by the pipeline proposed in this work, instead of being tested only in the explainability module. We have not carried out this test due to the high computational cost that would be involved in processing the thousands of reviews to be evaluated using GPT3. Another interesting possible line of future work would be to broaden the scope of the survey, both in terms of the number of products involved and the number of reviews, in order to clarify the conclusions reached at the forward simulation stage. Lastly, it would be very useful to try presenting the explanations issued by SHAP in a more familiar or natural format for the end user, so that we can see if their level of preference is increased for the general public. Acknowledgements This work was supported in part by grant Machine Learning on the Edge - Ayudas Fundación BBVA a Equipos de Investigación Científica 2019 ; the Spanish National Plan for Scientific and Technical Research and Innovation (PID2019-109238GB-C22 and TED2021-130599A-I00); the Xunta de Galicia (ED431C 2022/44) and ERDF funds. CITIC, as a Research Center of the University System of Galicia, is funded by Consellería de Educación, Universidade e Formación Profesional of the Xunta de Galicia, Spain through the European Regional Development Fund (ERDF) and the Secretaría Xeral de Universidades (Ref. ED431G 2019/01). This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

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