Java API for kdb+

| May 31, 2018

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The Java programming language has been consistently popular for two decades, and is important in many development environments. Its longevity, and the compatibility of code between versions and operating systems, leaves the landscape of Java applications in many industries very much divided between new offerings and long-established legacy code.

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The 6 Biggest AI Marketing Challenges & Their Solutions

Article | July 8, 2021

More and more businesses are utilizing modern-day opportunities that Artificial Intelligence (AI) brings to the digital world. Perhaps, it is the most necessary step for the companies to stay competitive in 2021 and beyond. With the rise of technology, AI-powered marketing platforms are becoming more common and simpler to use. However, this does not mean that they do not have any challenges. A survey conducted by Teradata, a data analytics firm, reports that around 80% of enterprise-level organizations have already embraced some form of AI. Out of them, approximately 32% of businesses use AI algorithms for marketing purposes. However, more than 90% of these companies have already anticipated significant barriers to adopt and integrate AI. In this article, we shed light on the six biggest challenges in AI marketing. It will help you act and avoid common problems if you encounter such roadblocks when integrating AI into your marketing strategy. Here are some highlights of this article: Many popular media sources have created hype around AI. Therefore, people, in general, don’t trust it. There isn’t enough skilled workforce to fill AI-related positions in organizations. AI software needs high-quality data. Unfortunately, maintaining such data quality is not that easy. AI software needs significant investment. Many small businesses lack IT infrastructure resources. Cloud services help them overcome this problem. As you can now understand, most challenges in AI marketing revolve around business alignment, data, or people. While every organization varies and will face the AI adoption process differently, there are a few common challenges in AI marketing you should be aware of. So, without further ado, let’s take a look at the most common AI challenges that digital marketers face. Lack of Knowledge of AI Systems When it's about total AI implementation, your company’s management must have a deeper understanding of the role of AI in Digital Marketing, the latest AI trends, data challenges, and all other essential aspects. However, many marketers lack a proper understanding of the use of AI technologies in marketing. On top of this, unfortunately, AI comes with a variety of fears and myths. While some people think they need an in-house data science team for complete AI adoption, others believe in those sci-fi fantasies showing how smart robots can end humanity. Insufficient knowledge of AI is one of the biggest challenges in AI marketing. It hinders the AI implementation in several ways and ultimately delays the success. How to get rid of this? First things first — start by acquiring knowledge. It might sound a bit demotivating, but we do not mean you have to be a data scientist for this. You can look at other giants in the industry, carefully analyze how they are deploying AI into their business, and act accordingly. Next, know more about the current AI technologies for marketing — you can either DIY or get help from an expert. Once you have adequate knowledge about it, you know what to expect from AI and what not. Challenges in Integration Deployment and integration of new technology requires skills. Integrating Artificial Intelligence into your business is not an easy task. It is a complicated job and requires proper knowledge. You first have to set up interfaces and other elements to address all your business needs. Such steps may require complex coding. Developers must consider feeding the data into the system, labeling, data storage, data infrastructure needs, and much more while setting up the elements. Then comes the model training and testing part. It is necessary for the following reasons: To check the effectiveness of your AI Develop a feedback loop for constant improvement Data sampling for reducing the stored data and run models even faster The biggest challenge here is — how to confirm if it's working correctly? And, is it worth the money you are investing? Arguably, the only and the most effective way to overcome this hurdle is to work closely with your vendor to ensure that everyone is well aware of the process. Plus, there should not be any limitations in the vendor’s expertise. They should be capable of guiding you beyond building the AI models. When you implement Artificial Intelligence with the right strategy, you indirectly reduce the risk of failure. And, once you successfully implement AI into your system, you will still have to educate your marketers to use it efficiently. In this way, your people can understand how to interpret the results they receive by proper implementation and effective use of the AI model. Poor Data Quality or Lack of Data High-quality data is essential for Artificial Intelligence. Any AI system will come up with poor results if you provide it with insufficient or poor-quality data. As the Big Data world is evolving every day, businesses are gathering vast amounts of data. However, this data is not always up to the mark. It's either insufficient or not good enough to drive a profitable AI marketing strategy. Such data-related challenges in AI marketing prevent companies from capitalizing on Big Data. For this reason, as a business, you should always make sure the data you get is clean and rich in quality. Otherwise, you will experience unsatisfactory results from the AI, and it will negatively influence the overall success of your AI-powered marketing campaigns. Budget Constraints for AI Implementation Many companies lack the necessary budget for implementing AI into the system. Even though AI has the power to provide impressive Returns of Investment (ROI), hefty investments are still one of the biggest challenges in AI marketing, especially for smaller and mid-size companies where the budgets are already stretched. AI-powered platforms come with high-performance hardware and complex software. And, the deployment and maintenance of such components are costly. Such budgeting challenges in AI marketing can limit the opportunities for businesses to utilize AI technology to the fullest. Thankfully, this is now becoming a thing of the past as many affordable AI vendors are coming ahead for the rescue. With them, you do not have to invest in developing in-house solutions. Moreover, they allow you to implement AI tech in a relatively cheaper and faster way. Privacy and Regulations Artificial intelligence is still new to this world, and it's growing at an incredible pace. Chances are that the rules and regulations surrounding AI will change and tighten up over the coming days. The data collection and use of data policies already impact businesses that collect and use data from the customers based in the European Union and drive their Artificial Intelligence systems. The EU implemented GDPR in 2018, and it has made the data collection, and data usage rules even stricter for companies. Ultimately, companies now have to be extra careful while collecting and using customer data. Furthermore, several businesses are restricted from storing the data offsite for regulatory purposes. This means that they can no longer utilize cloud-based AI marketing services. Constantly Changing Marketing Landscape AI is a new marketing tool and can bring disruption to traditional marketing operations. For this reason, marketers evaluate how AI can create new jobs and, at the same time, replace older jobs. One survey suggests that AI marketing tools are more likely to replace the jobs of around 6 out of 10 marketing analysts and marketing specialists over the coming years. Overcoming The Challenges in AI Marketing Yes, such challenges in AI marketing can sometimes slow down your campaigns and affect the outcomes of your AI-driven software. But fortunately, there are a variety of alternative solutions. You need to consider the following steps to rule out the common challenges in AI marketing we discussed earlier. Develop a target oriented marketing strategy Get the money before you roll out AI in marketing Train your marketers Recruit the right talent Developing business cases, recruiting talented marketers, measuring the ROI, and getting the required investment — probably, none of these steps sound interesting. But, when it is about the reality check of your AI marketing strategies, they are absolute methods that can open the door to actual Artificial Intelligence payoffs. In the end, every company's responsibility is to make sure that they are using the AI system responsibly so that they can benefit their customers in the best way possible. Frequently Asked Questions How does AI affect marketing? AI helps marketers to spot the latest internet trends and predict them for the future. Such trends are necessary to learn the current marketing facts and eventually help with significant tasks such as budget allocation and setting up the target audience. Plus, AI effectively reduces the money and time usually spent by companies on digital advertising. Simultaneously, it leads businesses towards smarter and more targeted advertising campaigns. As a result, many companies have implemented AI into their digital marketing strategies as it can increase sales and save money at the same time. On a bigger scale, AI has an impact on global trends, sustainability, and scalability. Even government issues, major public concerns, and major cities around the globe have seen positive effects of AI. AI can make the world a better place if used in the right way! How is AI used in digital marketing? Companies are utilizing some stand-out developments for improving the customer experience with the proper use of AI. For example: Image recognition technology Predictive and targeted content Content creation Chatbots With these, AI enhances customer support, and provides more relevant and targeted content to the customers. Why is artificial intelligence critical in marketing? With the correct use of Artificial intelligence, businesses can collect, analyze and store a large amount of data. As a result, AI is the best way to learn the latest marketing trends and incorporate them into your marketing strategy. In general, Artificial Intelligence has the power to help your company reach potential customers and provide them with easy access to make purchases. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How does AI affect marketing?", "acceptedAnswer": { "@type": "Answer", "text": "AI helps marketers to spot the latest internet trends and predict them for the future. Such trends are necessary to learn the current marketing facts and eventually help with significant tasks such as budget allocation and setting up the target audience. Plus, AI effectively reduces the money and time usually spent by companies on digital advertising. Simultaneously, it leads businesses towards smarter and more targeted advertising campaigns. As a result, many companies have implemented AI into their digital marketing strategies as it can increase sales and save money at the same time. On a bigger scale, AI has an impact on global trends, sustainability, and scalability. Even government issues, major public concerns, and major cities around the globe have seen positive effects of AI. AI can make the world a better place if used in the right way!" } },{ "@type": "Question", "name": "How is AI used in digital marketing?", "acceptedAnswer": { "@type": "Answer", "text": "Companies are utilizing some stand-out developments for improving the customer experience with the proper use of AI. For example: ● Image recognition technology ● Predictive and targeted content ● Content creation ● Chatbots With these, AI enhances customer support and provides more relevant and targeted content to the customers." } },{ "@type": "Question", "name": "Why is artificial intelligence critical in marketing?", "acceptedAnswer": { "@type": "Answer", "text": "With the correct use of Artificial intelligence, businesses can collect, analyze and store a large amount of data. As a result, AI is the best way to learn the latest marketing trends and incorporate them into your marketing strategy. In general, Artificial Intelligence has the power to help your company reach potential customers and provide them with easy access to make purchases." } }] }

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Common B2B SaaS Marketing Challenges: Best Tips to Overcome Them

Article | July 8, 2021

There’s a lot of difference between consumer marketing and SaaS marketing. Unlike the traditional consumer marketing techniques, SaaS marketing is complex, unconventional, and has nothing physical to endorse. In simple words, B2B SaaS marketing does not involve physical items that can be easily promoted and popularized in the market. Consumer marketing has products like phones, washing machines, books, bread, etc. Marketers use creative commercials to promote them and ultimately reach the crowd. Consumers relate to such ads and commercials and memorize the products. On the other hand, B2B SaaS marketing has its own set of hurdles, and only solid marketing strategies can get rid of them. The B2B SaaS marketing is all about promoting software that is not as fun and thrilling as the consumer items. Its existence is non-physical, and marketers often struggle to convince customers to buy it. Eventually, they have to adopt some out-of-the-box marketing strategies to overcome such B2B SaaS marketing challenges. What are the Basic B2B SaaS Marketing Challenges? The SaaS marketing industry is rapidly growing and most marketers face a set of challenges. They have to promote and sell virtual products such as software which requires deep technical knowledge and proper analysis, along with a few unique marketing strategies. With all such critical B2B SaaS marketing challenges to deal with, it's quite interesting to develop and implement the right SaaS marketing strategy for long-term growth. Here are some of the basic B2B SaaS marketing challenges: The attitude of the customers is one of the most critical B2B SaaS marketing challenges. Unfortunately, traditional marketing strategies for SaaS cannot effectively target the emotional quotient of the customers. The entire management team typically makes the purchase decisions of such products, and not a single person. SaaS offerings are dynamic and change with time. Releasing newer versions or updates for the same product can lead to the delivery of redundant marketing messaging. Marketers get little time for convincing the customers. Due to the short sales cycles, it's quite difficult to close the deals within the available window. Users often get confused with SaaS core terms such as cloud computing. You need to ensure your marketing strategy is informative enough. It’s essential to know the exact niche to market your SaaS products. Additional B2B SaaS Marketing Challenges Finding Ways to Stand Out from The Crowd The major concern of your SaaS business is satisfying the customer needs without following the same marketing strategies your competitor is using. The SaaS marketing world is evolving every day and company owners spend sleepless nights over even the slightest tweak in a competitor’s design or marketing strategy. It is an already crowded niche and maneuvering the way through it is the responsibility of every SaaS marketer. Failure can prevent you from racing ahead and your competitor will win the customers and growth in the end. Acquiring Low-Value Consumers in Big Volume SaaS marketers get relatively fewer client leads due to shorter sales cycles. There’s no room for a mistake in such cases as it may delay the process. For this reason, B2B SaaS companies should consider targeting low-value consumers in significant volumes just like the traditional B2C companies. A unique inbound marketing strategy is the best way to reap all the benefits of this tactic. Earning Customer Loyalty The SaaS pricing model makes sure the payments are received on time. For getting new customers, this is the primary agenda of every SaaS marketer. However, there is equal importance of customer retention programs to generate more revenue. The growth in customer retention can lead to huge profits in the long run. In layman’s terms, you need a robust marketing strategy for catering to customer needs and, at the same time, preventing them from switching to other companies. It will benefit you in: Developing unique marketing campaigns to convince the customers Better engagement with your customers through social channels Offering enhanced solutions to customer issues Delivering value-added products When you have an effective and carefully planned marketing strategy, you have more chances of captivating the attention of devoted SaaS fans. Now, let’s discuss some knockout marketing tactics that will help you conquer the common B2B SaaS marketing challenges discussed so far. Best Tips & Strategies to Overcome B2B SaaS Marketing Challenges Offer Free Trials to Get More Customers When selling physical products, you won’t be interested in giving away the stuff for free and incurring a loss. You may consider offering a few free products to the retailer for advertising purposes but you definitely won’t offer free stuff in huge volumes even to the retailer as it's not economically infeasible. The same strategy needs attention in the case of SaaS products. And, giving free trials of the product is a renowned and widely approved SaaS marketing strategy for growth. This SaaS marketing plan is a tactical way for acquiring new customers and onboarding them. Using the term FREE in your plan is the most effective way to overcome SaaS challenges. Many B2B SaaS companies use the free model in a variety of ways. For example: Free trial without payment information Free trial with payment information 30/60/90-day free trial Limited feature free trial Trial-to-paid Freemium Free Trial Develop a Great Content Marketing Strategy Any SaaS marketing strategy cannot rule without a carefully planned content marketing strategy. However, organizing and presenting the SaaS information in the form of content is one of the biggest challenges in marketing. Even though this is a fundamental thing, it is often overlooked. SaaS companies should consider posting regular blogs that serve as a source of reliable information for the users. If people know your product well, they are more likely to make the purchase. Your SaaS marketing plan should be able to explore the power of content and market it in different forms. Marketers can use techniques such as content syndication to effectively deal with SaaS challenges by delivering critical content to customers. Market your content through tweets, blogs, webinars, and all other ways. Let Your Product Sell Itself Whether it's a consumer marketing strategy or a SaaS marketing strategy, its results depend heavily on the product quality. And, when it's about the products, you have to focus on the following crucial things: Incredible products Excellent customer support All the great SaaS marketing examples always excel in these two factors. When your products and support are up to the mark, the rest of the things automatically fall in line. Develop a state-of-the-art software product and provide remarkable customer support with or without goodies and gifts, and then experiment how this strategy becomes a game-changer for you in overcoming all the SaaS challenges. Give Reassurance and a Demo to Deal With Rapid Sales Cycles The short sales cycles are one of the biggest challenges in marketing the SaaS products. The purchasing process spans over a few days or weeks. This is extremely lower than the purchasing process period of B2B sales marketing. SaaS products change continuously. If there are delays in the sales process, the software may undergo several iterations during this time. As a result, you will need to give a demo and reassurance to SaaS customers who may turn away to avoid longer sales cycles. Final Words In summary, SaaS marketers must understand this authentic and logical advice — great products and excellent customer services are the foundation of every successful marketing strategy. And, this has the power to overcome all the challenges in marketing. Frequently Asked Questions Which tool should we use to overcome the SaaS challenges? The following are the tools you need to overcome B2B SaaS marketing challenges: LinkedIn Sales Navigator UserVoice Intercom Hunter Databox VWO ActiveCampaign TrueNorth Wistia Slack What are the best SaaS marketing examples? Here are the best SaaS marketing examples of 2021: Shopify Mint Apple Music Movable Ink Spotify Netflix Adobe Invision Amazon Prime What are the top 3 challenges faced by SaaS marketers? The following are the three biggest SaaS marketing challenges: Dealing with traditional complainers Building customer loyalty and trust Standing out in the crowd { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "Which tool should we use to overcome the SaaS challenges?", "acceptedAnswer": { "@type": "Answer", "text": "The following are the tools you need to overcome B2B SaaS marketing challenges: LinkedIn Sales Navigator UserVoice Intercom Hunter Databox VWO ActiveCampaign TrueNorth Wistia Slack" } },{ "@type": "Question", "name": "What are the best SaaS marketing examples?", "acceptedAnswer": { "@type": "Answer", "text": "Here are the best SaaS marketing examples of 2021: Shopify Mint Apple Music Movable Ink Spotify Netflix Adobe Invision Amazon Prime" } },{ "@type": "Question", "name": "What are the top 3 challenges faced by SaaS marketers?", "acceptedAnswer": { "@type": "Answer", "text": "The following are the three biggest SaaS marketing challenges: Dealing with traditional complainers Building customer loyalty and trust Standing out in the crow" } }] }

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AI TECH

Build The Truth Block By Block

Article | July 8, 2021

There is nothing new about fake news. It has been in existence for centuries, albeit without the scaffolding of support from social media. From housewives’ tales to gossip magazines, the Trojan horse to the misinformation around the D-Day landing site, fake news has been a rite of passage. The Russian military made this into a fine art with “maskirovka,” the doctrine gaining superiority through deception, denial and disinformation. However, it was the 2016 U.S. presidential election that branded it with a legit identity and with such alacrity that today, I find myself questioning everything I read or hear about, no matter the veracity of the source. Fake news is a contagion that has the potency to be as disruptive as the coronavirus and must be fought with equal urgency. If you cannot solve the problem, manage it. The power behind fake news is big data — the quantum of data generated and its velocity of distribution. Big data feeds companies with interesting consumer insights on evolving trends and behaviors, which are then beautifully packaged into text, video or audio content by harnessing machine learning and deep learning algorithms. The slips happen here. If I were to personify fake news, Cersei Lannister, the manipulative, power-hungry queen in Game of Thrones, would be the perfect candidate. Cersei embellishes the truth with dramatic twists and turns to create compelling lies. We experienced a similar situation when news broke that President Trump’s grandfather owned the Arctic Restaurant and Hotel in Bennett, British Columbia, during the 1890s and 1900s, which fueled an interesting twist on the source of the family's wealth. While AI will help us identify fake news, we need a preventive measure that nips it in the bud It is almost difficult to differentiate fake news from real news. While AI will help us identify fake news, we need a preventive measure that nips it in the bud — a vaccination rather than medication. If tech helps in creating an issue, should tech help solve it too? Based on my years of experience in implementing these solutions for large enterprises and developing next-gen blockchain offerings with startups, I believe blockchain may just be the remedy we are looking for. Most technologists, however, do not consider blockchain to be a relevant or credible technology, with the primary criticisms being its lack of widespread adoption and its esotericism. But I believe the contrary. The vision of grandma-proof blockchain is becoming real — to create an inclusive global, scalable blockchain solution that can cater to every human need. Blockchain should be our weapon to effectively reduce and ultimately eradicate fake news. In blockchain, no single individual or group holds the authority, but everyone needs to approve; therefore, it enables the highest degree of integrity, privacy and security Blockchain is nothing but a distributed ledger that helps build trust in decentralized networks and that runs on the computing power of its participants. No single individual or group holds the authority, but everyone needs to approve; therefore, it enables the highest degree of integrity, privacy and security. This is accomplished by consensus algorithms. Each blockchain has adopted some form of it, and some even claim to have consensus that can prevent obfuscation of the truth even when faced with over 90% malicious intent. Blockchain technology enables a "shared single version of truth" across multiple entities based on two fundamental characteristics: immutability and traceability. Immutability Immutability is when a blockchain ledger has the capability to remain unaltered, effectively ensuring that any data on the blockchain cannot be altered — only built upon. Each block created has a unique identity and timestamp attached to it that builds a fortress around the data. Innovative upcoming blockchains use crypto-biometric identity to further buttress the fort. For example, Mediachain, a decentralized independent music library, uses blockchain to protect the originator’s authenticity by providing information about the creator, producer and lyrics to listeners. Steemit is a decentralized social media site that rewards content creators who also interact with other users. Each content piece or interaction is recorded on the immutable record by blockchain. And if news companies were to adopt blockchain — and organizations like the New York Times are already working on this — this is what we might expect: Journalists could create a block (an entry in a distributed ledger) and upload news via text, image or video. Editors would then create another new block with an edited version of the news, leaving the original block unchanged. Publishers (news agencies) would then publish the news based on their block and any changes that they might make. Each one of the participants is authenticated on the blockchain with a simple touch of their finger while protecting the fidelity of the news. Remember, entries cannot be changed, only built upon, and therefore, each change is recorded and allocated to a specific entity. For someone to “fake” the news, they would have to alter the data at each level. Infiltrating the high-security protocols would require considerable time and resource allocations. Traceability As mentioned, each block that is created has a distinct identity attached, preferably a crypto-biometric for added security and individual control. So, if fake news is generated and circulated through social media using blockchain as the base, it becomes easier to pinpoint the culprit while establishing the real source of the news. This would ascribe true content ownership to credible creators. Fake news creators are using advanced tech stacks to create deepfakes for digital deception. Generative adversarial networks (GANs) can help them to create deepfakes of images and videos that can even counteract or deceive advanced AI/ML algorithms. Of course, GANs are also being used to detect fake news now. If technology has helped fake news become compelling and believable, let’s use intelligent and available technology like blockchain to at least control it, if not eradicate it. Then again, if blockchain had existed in the medieval ages, we would have been denied the entertaining antics of Cersei Lannister and the wonderful blockbuster series that kept most of us enthralled!

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Researchers use Artificial Intelligence to predict drug response in lung cancer therapies

Article | July 8, 2021

Researchers have used Artificial Intelligence (AI) to train algorithms and predict tumour sensitivity in three advanced non-small cell lung cancer therapies which can help predict more accurate treatment efficacy at an early stage of the disease. The researchers at Columbia University's Irving Medical Center analysed CT images from 92 patients receiving drug agent nivolumab in two trials; 50 patients receiving docetaxel in one trial, and 46 patients receiving gefitinib in one trial. To develop the model, the researchers used the CT images taken at baseline and on first-treatment assessment.

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Trace3

Trace3, a pioneer in business transformation solutions, empowers organizations to lead their market space by keeping pace with the rapid changes in IT innovations ensuring relevance to specific business initiatives required to maximize revenue generation by leveraging the latest Silicon Valley, cloud, big data and datacenter technologies maximizing organizational health.

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