<div>Aditi Gupta is a social entrepreneur working towards educating women about menstruation, menstrual hygiene, and the myths associated with it. She named her unique initiative, Menstrupedia. Menstrupedia Comic is a complete guide on periods.&nbsp;<o:p></o:p> Ms. Gupta is a World Economic Forum Global Shaper and made it to the achiever’s list of&nbsp;Forbes&nbsp;India 30 under 30 in 2014 to break the taboo around menstruation. She is an International Visitor Leadership Program (IVLP) alumni. Her work has been featured in&nbsp;The Wall Street Journal, Reuters, CNBC, and BBC. She aspires to create a future where menstruation is not a taboo but a welcoming change in a girl's life.<o:p></o:p>Aditi and her partner, Tuhin recently appeared&nbsp;on Shark Tank,&nbsp;India.&nbsp;We talk to her about her experience with the show.&nbsp;<o:p></o:p>What we see on television might be just a 10/ mins pitch, but it takes somewhere around 45 mins-2 hours for a pitch. Can you tell our audience what goes through into the process to appear on Shark Tank?<o:p></o:p>We received a random call asking us if we were looking for raising funds. In 2021, we were looking for funds and working on our pitch for investors. So, when we received this phone call, we thought okay let’s try it.<o:p></o:p>The whole process was in fact very smooth. After your application, if you go to the next round, they would connect with you again. In case they decide to not take your application forward at any stage, they would not connect with you. They receive a crazy number of application so they demand for you to respond very quickly. The application forms are very elaborative and exhaustive. Applying to shark tank would feel like an 8-hour job. The entire process is very elaborative which shows how much attention they pay to every detail. The team would guide you with how to move forward. If you qualify for the next stage of the application, I would suggest you to be completely dedicated to the application process.<o:p></o:p>The pitch could be cut between 10-20 minutes but you remain in the tank for about 1-2 hours. The sharks need to know a lot of details about you and your business before they invest in you. The team also ensures that they collect information regarding your background story, how your business model works, and all several other aspects. Before you appear in front of the sharks, there is a lot of documentation. A lot of conversation and discussion goes with the sharks.<o:p></o:p>To be very specific, the three main stages of the application process before you appear in front of the sharks include:<o:p></o:p>1. An elaborative application form 2. Two pitch videos, and 3. Audition round<o:p></o:p>For someone who gets to the next round, I would suggest them to be very patient and dedicated towards the entire process. The entire team works very dedicatedly, yet some delays must be expected.&nbsp; Be flexible, take up on their suggestions. One must understand that it is a television show and they would need to present certain things creatively to gain more traction.<o:p></o:p>&nbsp;Was your experience pitching in front&nbsp;of Sharks any different from pitching to other investors?<o:p></o:p>Pitching ideas in front of sharks was very heart warming and encouraging. When we went in the tank, the discussions were so friendly and they appreciated us for what we were doing. With other incubators, sometimes they end up bullying us.<o:p></o:p>We have been a part of two incubation program; they brand themselves as a pioneer in India. The mentor they assigned me ended up bullying me. I was so disheartened with the entire experience. After such experiences, we decided to not go for any of such programs. We were bootstrapped for 8 years.<o:p></o:p>But the experience with shark tank was amazing and I am excited to work with the sharks.<o:p></o:p>What was your reaction when one of the sharks suggested you become a ‘sanitary pad’ company? Is this something you might pursue in near future?<o:p></o:p>One of our major investors is a sanitary pad company, Stayfree. We help them reach their product to girls via our comic. An important chunk of money we receive is via Stayfree. I believe that we don’t need to be a sanitary pad company to sell it. We are one of the most innovative companies in the world to educate about periods. We would never want to change the basic idea for our company i.e., to educate people about things that don’t feel comfortable to talk about in open.<o:p></o:p>Did you have a specific shark in mind to acquire your investment?<o:p></o:p>Yes, Namita was our ideal investor and we are glad that she came on board with us. Apart from Namita and Vinita, it would have been difficult for other sharks to understand the importance of this business and of course the limitation of the business.<o:p></o:p>After the airing of the episode, how did it impact the sales or leads for Menstrupedia?<o:p></o:p>After the airing of the episode, there is a shark tank effect. We saw around 13% of increase in our sale. But we know it would fade away.<o:p></o:p>Apart from the sale, I would like to thank Shark Tank for the recognition we are getting. Our families are now more interested to understand how our business work; it opened up a passage for us to have many discussions with family and friends.<o:p></o:p>What would be the one factor that candidates wanting to be on the next season of Shark tank must understand?<o:p></o:p>This was Shark Tank’s first season in India and yet they got more than 62,000 applications. I am assuming that competition will be extremely tough for the upcoming seasons. My suggestion for aspiring candidates would be to respect the deadlines. Since they work with a huge amount of application, if you are proactive, it might improve your chances of getting in the next round.<o:p></o:p>Lastly, how would you rate the entire experience?&nbsp;<o:p></o:p>The entire experience was amazing. What differentiates shark tank from other incubators is that it is a very pro-entrepreneur show. Everybody will be rooting for you.<o:p></o:p>The team is extremely talented. Sharks and pitchers are a small part of the process that you see. The team is truly invested in bring entrepreneurs idea out in the world. They work along with you to improve your story telling skills, presentation skills, language, performance, and many factors that might impact your pitching.<o:p></o:p>&nbsp;Can you share some advice for young entrepreneurs? I would recommend to go for investors who bring additional benefits to you apart from money. Someone who would help you grow as an entrepreneur, improve your distribution channels, gets you more connections, and how you can multiply the money.<o:p></o:p>An entrepreneur understands his/her business the best. If you get repeat sales and low customer acquisition; it indicates towards profitability. Make sure that you focus on profitability and how you can improve your customer experience. Be obsessed with solving customer issues.&nbsp; As an entrepreneur, I would recommend that instead of focusing on impact and status, focus on profitability. When you start to multiply money, more people would be interested in you and your business.<o:p></o:p>&nbsp; What is the common psychology of the investors?<o:p></o:p>If someone is investing in your business, they would need their money to be multiplied. Having a great business plan and your business is very profitable, do not fall for the fallacy of creating an impact. If you are successful and reach a million people, eventually you will create an impact.<o:p></o:p>&nbsp;<o:p></o:p></div>

Techfastly

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Healthcare

In Conversation with Aditi Gupta, Founder of Menstrupedia

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Cryptocurrency

Step into the Superworld with Hrish Lotlikar Co-Founder & CEO, SuperWorld

<div>What started as a read-only medium of gathering information in the 80s, the World Wide Web(WWW) has evolved into a humongous new avatar, Web 3. Today, we are at a transition phase wherein web 2 and web 3 are contemporary to each other – with web 2 slowly phasing out and web 3 taking center stage. From IoT to blockchain, web 3 has started to take place in our lives, and the influence is going to increase in the years to come. We already see people getting attracted to the likes of Decentralised Finance and the world of Metaverse gradually. Innovation in the field of IoT by Samsung, Apple, etc., is also gaining popularity. Looking at the opportunity, even Facebook rebranded itself as Meta! Let's learn about the top ten big tech companies and how they are adopting Web 3 technology. &nbsp;Meta<o:p></o:p>Ever since Facebook rebranded itself, Meta has created a lot of buzz around VR, AR, Metaverse, and what the future might look like. Although its experiment with cryptocurrency didn’t work, the development of Metaverse with the oculus ecosystem is well known. According to the USPTO, US Patent and Trademark Office, the company has filed eight new trademark applications regarding various web3-related projects, including cryptocurrencies and the Metaverse. It is actively working to integrate social media, Decentralised Finance, and Virtual Reality. Head of Instagram, Adam Mosseri, has also announced its plans to bring in NFTs on Instagram and Facebook.<o:p></o:p>&nbsp;Twitter<o:p></o:p>Although it seems like Twitter is divided on its approach to adapting web 3, with Elon Musk and Jack Dorsey both openly criticizing it, the platform has identified the growing buzz among its users about cryptocurrency and NFTs. Twitter Blue users can even add an NFT as their profile picture. This adoption might hint at which direction the company might be moving.<o:p></o:p>&nbsp;Oracle<o:p></o:p>Leading cloud computing platform Oracle has come up with a blockchain service. A description of Oracle blockchain on their website reads, “Blockchain provides a collaborative framework for sharing reliable data. Oracle offers easy ways to adopt blockchain technology, including a cloud service, an on-premises edition, and a SaaS application for the supply chain.” Oracle has plans to diversify its blockchain platform through smart contracts, distributed ledger technology, and so on. It also provides tutorials for enterprises to adopt tokenization and the latest blockchain technologies in cloud computing.<o:p></o:p>&nbsp;Samsung<o:p></o:p>Samsung’s support for dapps and blockchain-based games is well known. A leading player in the IoT segment, it is also well known for delving into the Metaverse with the successful launches of Samsung 837X, their immersive Metaverse experience in Decentraland, and Samsung Superstar Galaxy on Roblox. Recently, it also launched the Samsung US in Discord, which is a leading platform for web 3 itself. The Samsung US Discord server is specially designed as a fun, interactive way for fans, gamers, and creators to interact and get exclusive access to products, events, non-fungible tokens (NFTs), and other Web3-based wonders. “Virtual communication platforms, like Discord, enable us to cultivate a community where both current Samsung enthusiasts and brand new fans can unite. As these enthusiasts anticipate an NFT drop, exclusive product giveaway, or virtual event, we get to explore this new frontier alongside them, allowing us to experiment, learn and ultimately, shape our Metaverse future – it’s tremendously exciting,” said Michelle Crossan-Matos, CMO, Samsung Electronics America.&nbsp;<o:p></o:p>&nbsp;Google<o:p></o:p>Google is a frontrunner in making affordable VR goggles accessible to the masses with its Google cardboard. We can also see the increased application of VR and AR technologies in the latest Android smartphones. However, web 3 is not only about VR, AR, and Metaverse; it also promotes a decentralized way of doing things that don’t go well with the business models of some of the tech giants, including Google. We have seen it somehow side-lining itself from the Web 3 technology. Although Sundar Pichai has shown interest in checking out methods for blockchain technology to include higher assistance to popular services such as Google Maps and YouTube, and in discovering methods to “support customer needs” through blockchain-powered platforms, we are yet to see Google delve deep into Web 3.<o:p></o:p>&nbsp;Tesla<o:p></o:p>Tesla’s Web 3 plans are greatly publicized. It is one of the forerunners in IoT integration in cars. Moreover, by developing AI systems for driver assistance and innovation in self-driving cars, Tesla shows its interest in the wave. It is also one of the first car companies to accept payment in cryptocurrencies. Moreover, it is supposed to deploy blockchain technology to provide a platform that aims to create a “open, transparent, and global registry” to track cobalt from mine to battery, assuring that the volume of any traceable material is accounted for in the production of EV batteries.<o:p></o:p>&nbsp;Nvidia<o:p></o:p>Nvidia is among the leaders in developing the infrastructure that powers web 3. Recently, it has partnered with Flux to bring Web 3 to “the next level”. Flux is an ecosystem and suite of decentralized computing services and environment agnostic development systems for building decentralized applications according to developer preferences. Nvidia produces powerful computing chips needed for integration with web 3.<o:p></o:p>&nbsp;Microsoft<o:p></o:p>Microsoft has recently partnered with Astar Network, which is a Polkadot Smart Contract Hub for WASM and EVM. has announced that it will assist Astar Network in building and implementing the Web3 future through the Astar Incubation Program. It is supposed to assist businesses in adopting Web 3 technologies. Microsoft is also the newest investor in Ethereum co-founder ConsenSys. Recently, its acquisition of Activision Blizzard also created a lot of buzz around its dive into Metaverse.<o:p></o:p>&nbsp;Amazon<o:p></o:p>Much like Oracle, Amazon too is delving into Web 3 with its web services venture. In March 2021, Amazon Web Services announced the availability of Ethereum on Amazon Managed blockchain — a fully-managed service that allows users “to join public networks or set up and manage scalable private networks using popular open-source frameworks.”<o:p></o:p>&nbsp;Sony<o:p></o:p>It is somewhat apparent that the creator of the PlayStation gaming ecosystem will delve into Web 3 technology, with Metaverse becoming more popular day by day. Last year, Sony filed many patents that would allow it to accept cryptocurrencies for e-sports betting in-game. Sony has plans to integrate the technology not only in PlayStation but also in consoles made by other brands, especially in VR headsets. Consequently, it also has plans to develop infrastructure for NFTs.<o:p></o:p>&nbsp;More and more companies are investing in Web3 ventures. According to Crunchbase numbers, last year saw about $17.9 billion invested in 1,312 deals in blockchain-related startups. That number dwarfed the $2.1 billion in 790 deals in 2020 and even the former high of $4.4 billion in 1,223 deals witnessed back in 2018.<o:p></o:p>&nbsp;Change is constant, and Web 3 is the latest wave of change in how the Web works. Although what we expect from and imagine of Web 3 is far from materializing, a major concern remains in making it accessible to the common people. The development of 5G in developing countries will certainly boost its adoption.<o:p></o:p>&nbsp;</div>

10 Big Tech Companies and How They Are Adopting Web3 Technology

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Artificial Intelligence

eBPF to Enhance Kubernetes Monitoring

<div>Liz Rice is Chief Open Source Officer with eBPF specialists Isovalent, creators of the Cilium cloud native networking, security and observability project. She was Chair of the CNCF's Technical Oversight Committee 2019-2022, and Co-Chair of KubeCon + CloudNativeCon in 2018. She is also the author of Container Security, published by O'Reilly.<o:p></o:p>&nbsp;<o:p></o:p>She has a wealth of software development, team, and product management experience from working on network protocols and distributed systems, and in digital technology sectors such as VOD, music, and VoIP. When not writing code, or talking about it, Liz loves riding bikes in places with better weather than her native London, and competing in virtual races on Zwift.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: Most of our readers might not understand the kernel. Can you explain what the kernel does?</h4>Operating systems have two parts: userspace and the kernel. Userspace has lower privileges; kernel space is a fully privileged environment. The kernel is the only part that can directly access memory, files, network, or any other hardware component. Userspace applications where we typically operate have to ask the kernel to do things on its behalf.<o:p></o:p><o:p>&nbsp;</o:p>As developers, we write application software; and applications run in userspace. If you're writing an application and want to read from a file, send a network message, or display something to the screen, you can't do it directly; you have to ask the kernel to do it for you. Usually, that's hidden from you because we have language abstractions that hide the interface. But in practice, your application is making system calls to ask the kernel to act on its behalf. The kernel is also doing things like scheduling multiple applications to run concurrently.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: How does the userspace interact with the kernel space?</h4>There is an API called the system call or syscall interface, and there are over 300 different system calls. In most programming languages, we don't write directly to the system call; there's usually an abstraction. In the world of C, we talk about the standard library, and many other languages build on top of that. For example, if you open a file, you probably have a language-specific function called 'open'. When you call that, underneath the covers, it will make a system call to an open syscall to open that file on your behalf.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: What is packet filtering? What is Berkeley packet filtering? And what is the extended bit in it?</h4>Okay, so this is a bit of a history lesson. Berkeley packet filtering was a paper written from the Berkeley Lab; that's where it gets the Berkeley part of the name. The idea was that as packets arrive into the kernel you might want to take a copy of certain packets to examine them in user space, that's packet filtering. But packet filtering is just a small part of what we now call BPF and eBPF, so honestly the acronym isn't all that helpful today.<o:p></o:p><o:p>&nbsp;</o:p>eBPF is a way of running custom code within the kernel. Normally, we write applications that run in user space, but with eBPF, we can run custom programs within the kernel, load them dynamically, attach them to kernel events, and change the behaviour of the kernel.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: Earlier, you mentioned that userspace is a less privileged environment. If eBPF programs are running and allowed to manipulate the packet in userspace, a function normally reserved for kernel space programs,&nbsp; isn't there a security aspect to it?</h4>The first thing is that it has to be treated with respect. If you allow someone to load eBPF programs, they need to be privileged. There is a Linux capability called CAP_BPF that you need to give people the same way you would give out root privileges; you have to treat it like root. If someone can load eBPF programs, they can do anything on your system.<o:p></o:p><o:p>&nbsp;</o:p>The thing that makes BPF programs safer than kernel modules is the 'eBPF verifier'. Whenever you load an eBPF program into the kernel, it goes through a verification step. It makes sure that it's safe to run the program, and it would definitely reach a conclusion, i.e., it's not going to loop indefinitely. It's never going to dereference a null pointer because that would make it crash; the whole machine dies if you crash the kernel. It also checks that any memory access is as expected. For example, if you've attached an eBPF program to receiving network packets, you're only allowed to look at the network packet's memory. You can't just look at arbitrary memory across the system. So, the verifier makes sure that programs will be safe to run and that they're doing sensible memory access.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: If eBPF is so powerful, why is the industry still following the sidecar pattern for service mesh and agents for monitoring? What is preventing the industry from moving to eBPF?</h4>&nbsp;That's exactly what we're doing with the Cilium project. Cilium enables networking, visibility, and security using eBPF and without needing sidecars. There are other examples of eBPF enabled networking. For example, Facebook has built a load balancer called Katran, and Cloudflare has eBPF-enabled load balancers too. It has taken time for eBPF networking to be widely adopted, because you need eBPF support in the version of the Linux kernel that you're running. It can take several years for functionality in the Linux kernel to make it into a Linux distribution. Maybe two years ago, not everybody could really use eBPF, because they were using older kernels that pre-dated eBPF, but now it's so widespread. That's why eBPF has really taken off in the last year or two.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: What are the advantages and what are the drawbacks of eBPF for routing and observability in cloud native?</h4>eBPF, particularly for Kubernetes networking and container networking, turns out to be a real performance improvement. And the reason for this is that when you run containers, or Kubernetes pods, you typically have a network namespace for each pod. It has its networking stack in that network namespace, and there is also a network namespace on the host with its own network stack. Suppose you imagine a packet arriving physically at a machine through the host's network interface, a physical network card. In a traditional networking setup the packet will go through the host's networking stack, then it gets forwarded to a virtual network connection into the pod where it has to go through another network stack in that pod, to arrive at the application.<o:p></o:p><o:p>&nbsp;</o:p>With eBPF, we can hook in as soon as the packet arrives; We can look at the destination address, recognize that it's going to a pod and send it directly to that virtual ethernet connection for the pod, bypassing the host's networking stack. That makes it dramatically faster than the traditional networking approach. It is almost as fast as if you were running networking just from one node to another without any containers at all. And we can also collect observability data about network flows, and provide security controls really efficiently using eBPF.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: Wonderful! It looks like eBPF is a real game changer! We can save a lot of operational dollars by delegating their observability and routing needs to eBPF! But how do we do it?</h4>So the good news is you can very easily install Cilium on all of the cloud providers. Google already uses Cilium as the default for the GKE data plane. Amazon uses Cilium as the default data-plane for EKS anywhere. Alibaba Cloud uses Cilium as well. A lot of managed Kubernetes services are also opting to use Cilium as the network implementation, now that kernel support for eBPF is so widespread, and because there are a lot of performance benefits from using eBPF based networking - and Cilium is a really good implementation.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: If eBPF is so powerful, why is the industry still following the sidecar pattern for service mesh and agents for monitoring?</h4>I would say take a look at Cilium, as we have sidecarless service mesh in beta right now. Because it's in beta, I wouldn't say upgrade all your Production nodes just yet! But that's coming very soon. And what we've done with the eBPF-based service mesh is, we already talked about the kind of networking performance improvements that we can have, but we can also make resource savings by avoiding sidecar injection. In service mesh, we have this extra proxy component that's normally injected into every single pod. And that creates overhead. If you've got, let's say, 1000 pods in a cluster, routing information has to be duplicated in 1000 sidecar proxies. And you also have this extra networking step that you need to send every packet through. By using an eBPF-based data plane, we can avoid having to inject the proxy into every single pod, we can just have one proxy per node. So it's much more efficient from a routing table point of view, and it's much more efficient from a network path point of view. And yeah, so keep an eye on the Cilium service mesh beta, because that's going very well, we have an Ingress implementation and although it's early days we're seeing some really good performance numbers. There are a few features that will be coming in future releases, like SMI integration. But yeah, it's very promising.<o:p></o:p><o:p>&nbsp;</o:p><h4 style="margin: 0cm; font-size: 12pt; font-family: Calibri, sans-serif; color: rgb(0, 0, 0);">Q: What is your advice for people getting started in open source?</h4>I would say find a good and welcoming community. Kubernetes has a really strong community, there are lots of other CNCF projects that are very welcoming. Look for projects that excite you, and that you want to get involved with and ideally if it's interesting for your current employer, that's helpful from a career point of view.<o:p></o:p><o:p>&nbsp;</o:p>Don't be afraid to raise your hand and ask your questions.<o:p></o:p><o:p>&nbsp;</o:p>Find the Slack channels, discord channels, GitHub repos, and don't be afraid to ask for help. The best open-source communities are really very supportive.<o:p></o:p></div>

Premium reporting on technology, startups, VC funding, and software from Techfastly tagged with Data Science. Read all about Data Science here.

Data Science

In Conversation with Liz Rice, Chief Open Source Officer at Isovalent

Artificial Intelligence (AI) has the potential to transform businesses, but widespread adoption faces several barriers. In this article, we discuss the common challenges and provide actionable steps to overcome them, including lack of understanding, data quality and availability, cost and ROI concerns, ethical and regulatory challenges, and culture and organizational readiness. Read on to learn how to harness the power of AI and position your business for success in the digital era.

Artificial Intelligence (AI) is a hot topic in the business world, with the potential to revolutionize operations and drive growth. However, many organizations face significant barriers to wider AI adoption. These challenges can range from lack of understanding and expertise to cost and ROI concerns, ethical and regulatory challenges, data quality and availability, and culture and organizational readiness.

Overcoming Barriers to Wider Adoption of Artificial Intelligence

Breaking the Barriers: How to Overcome Challenges in Wider Adoption of Artificial Intelligence

Artificial intelligence (AI) has long been touted as the disruptive force that will revolutionize how businesses and organizations operate. From heightened efficiency to improved decision-making, the potential benefits of AI are undeniable. Despite the hype, however, widespread adoption of AI has been sluggish across various industries and countries, with many organizations reluctant to embrace the technology entirely. In this piece, we will explore the primary impediments to broader AI adoption and proffer strategies that organizations can employ to surmount these barriers.<h2>Lack of Understanding and Expertise</h2>When it comes to adopting AI, one of the biggest challenges that businesses face is a lack of understanding and expertise. AI is an incredibly complex and sophisticated field that requires specific knowledge and skills. Unfortunately, many organizations may not have the necessary skills and expertise to develop and implement AI solutions. In fact, according to a recent survey, only 15% of CEOs claim that their organizations have deployed AI across multiple departments or units.This lack of understanding is a major barrier to AI implementation, with 77% of executives citing it as the top obstacle. However, businesses can overcome this challenge by investing in training and education to develop internal AI skills. This can include hiring data scientists and AI professionals or upskilling current employees. The good news is that the need for AI specialists is on the rise, with a 74% increase in the number of AI experts year on year over the last four years. Additionally, enterprises can collaborate with external AI specialists and consultants to create and implement AI solutions that fit their specific requirements. By developing AI expertise, organizations can overcome this obstacle and unlock the numerous benefits of AI, including increased efficiency, productivity, and decision-making.<h2>Data Quality and Availability</h2>AI relies on vast amounts of high-quality data to learn and make accurate predictions. However, many companies struggle to access and manage their data effectively, and may possess low-quality data that is unsuitable for AI applications.According to an O'Reilly Media survey, data quality and availability are the primary challenges for firms attempting to implement AI. The survey revealed that 63% of respondents identified data quality as a significant hurdle, while 55% cited data availability as a critical challenge.To overcome this obstacle, businesses can focus on improving their data management systems and investing in data quality initiatives. This may involve implementing data governance frameworks, ensuring data privacy and security, and utilizing advanced data analytics technologies to clean and prepare data for AI applications.<h2>Cost and ROI</h2>The perceived cost and return on investment (ROI) are significant barriers to AI adoption for businesses. AI initiatives can require substantial investments in terms of technology, infrastructure, and human resources, and the ROI of AI projects may not always be clear.In a Deloitte report, the top two factors that firms consider when deciding whether to implement AI are cost and ROI. The report found that 47% of executives see cost as a significant obstacle to AI adoption, while 44% cite uncertainty about ROI.To address this issue, businesses should approach AI projects with a clear understanding of the potential benefits and risks. They should conduct comprehensive cost-benefit analyses and ensure that AI projects align with corporate goals and priorities. By doing so, they can make informed decisions about AI investments and maximize the potential ROI of these initiatives.<h2>Ethical and Regulatory Concerns</h2>As artificial intelligence becomes more prevalent, there is a growing concern about its ethical and regulatory implications. Improperly built and deployed AI systems can lead to bias, discrimination, and privacy concerns. In addition, a lack of legislative frameworks and norms governing AI makes it difficult for businesses to address legal and ethical concerns.According to a recent PwC survey, 68% of corporate leaders are concerned about the ethical implications of AI deployment. To tackle these challenges, companies should prioritize ethical and responsible use of artificial intelligence. This involves establishing clear guidelines and principles for AI development, testing AI systems for potential biases, and incorporating transparency and explainability into AI algorithms.Furthermore, companies can collaborate with industry organizations and policymakers to advocate for responsible AI frameworks and regulations. By taking a proactive approach to ethical concerns, businesses can avoid reputational damage and reap the benefits of AI in a sustainable and responsible manner.<h2>Culture and Organizational Readiness</h2>Finally, culture and organizational preparation are important barriers to AI deployment. AI necessitates a mindset and cultural transformation, emphasizing experimentation, agility, and constant learning. Many firms may lack the culture or infrastructure to accommodate these changes, or they may meet pushback from hesitant employees.According to an MIT Sloan Management Review survey, 40% of respondents identified corporate culture and reluctance to change as the most significant barriers to AI adoption.Businesses should create a culture of innovation and experimentation to overcome this difficulty. They should encourage employees to learn about and embrace AI, provide training and development opportunities, and create a supportive and collaborative environment for AI initiatives. Additionally, businesses can use pilot projects and proof-of-concept initiatives to demonstrate the value of AI and build momentum for broader adoption.<h2>Conclusion</h2>Artificial Intelligence (AI) is a game-changer for businesses looking to boost productivity, efficiency, and innovation. However, embracing AI can be challenging, and many organizations struggle with several roadblocks, including lack of expertise, data quality, cost, ethics, and culture.To harness the potential of AI, businesses must first invest in education and skills development. This means hiring data scientists and other experts who can help identify opportunities for AI and develop a strategy for implementing it. Another critical factor is data management. Organizations must upgrade their data quality and management practices to ensure that they can extract meaningful insights from their data and feed them into AI systems.Cost and ROI concerns are also a significant barriers to AI adoption. Companies must do extensive cost-benefit evaluations to determine the potential return on investment for AI projects. In addition, ethical and regulatory challenges are another issue that businesses must address. These challenges include issues of fairness, accountability, and transparency, and companies must ensure they adhere to ethical guidelines and regulations.Finally, culture and organizational readiness are also critical factors in successful AI adoption. Businesses must cultivate an innovative and experimental culture that encourages employees to learn about and embrace AI, and provide training and development opportunities to support AI initiatives.By overcoming these challenges, businesses can reap the benefits of AI, such as increased productivity, enhanced decision-making, and improved customer experiences. As AI evolves and becomes more widespread, companies that embrace it will be better positioned to compete and thrive in the digital era.

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