Adopting Software-Defined Networking in the Enterprise

SRIDHAR MAHANKALI,SANJAY RUNGTA | April 26, 2016

article image
Intel IT is adopting software-defined networking (SDN) to enable on-demand provisioning of networks and network services. By virtualizing the network through a programmable interface, we can offer better support for internal customers—Intel application developers—who work in a fast-paced agile development environment. These customers need to be able to access network resources without having to negotiate a bottleneck created by configuring networks and provisioning services.

Spotlight

Teralytics

The better we understand the way we move, the better we can build cities, mobility services and transportation systems to meet our needs. Teralytics offers the most advanced insights on human mobility based on cutting edge data science, proprietary machine learning algorithms and deep technology, capturing billions of signals every day from cell towers and other unique sources. We work with leading telecom companies and data partners around the globe to capture information about people’s geographical locations, movement habits and demographics; all completely anonymized and aggregated.

OTHER ARTICLES

Why Humans Need Chatbots And Chatbots Need Humans

Article | July 1, 2020

Chatbots have come a long way in the past few years. The improvements in technology have enabled developers to expand on bot capabilities far beyond just functioning as a FAQ. Today, the automation of chatbots can process orders, perform financial transactions, make bookings, and much more. (Check out other intelligent functions here.) However, as intelligent as bots can be, no chatbot can handle and resolve all your customer queries. It simply cannot answer the infinite number of questions a human may throw at it. The technology is simply not there yet, and it may never truly get there. But perhaps more importantly, brands shouldn’t want a bot to manage every customer query. A bot working independently of human involvement won’t always deliver the best results for customer or agent. It’s the combination of chatbots and human agents that takes customer service to new heights. What you need is a smart and efficient way of translating your organization’s unique customer service philosophy into appropriate action so that every question is met with an answer in the best way possible – whether that be by bot, human agent, or a blend of both. To deliver this, you have to pay attention to the who, what, when, and where of customer engagement. You need to know who your highest-value customers are so you can always route them to a human agent, for example. You need to know what they need help with so a simple question can be managed by a bot. And the list goes on. Here’s why humans need chatbots, and chatbots need humans – and how you can achieve this perfect balance to deliver support that will exceed customer expectations and generate substantial ROI. Why humans need chatbots There’s no doubt that supplementing customer-facing roles with automation can yield fantastic results. The launch of McDonald’s self-serve kiosks is a great example of this. By giving customers the option of ordering their meal through a kiosk, or through a cashier, McDonald’s demonstrates the success you can achieve by combining automation with human. Here are just some of the benefits it brought to the customer and employee experience: 1. Automating large portions of simple queries so workers have more time to focus on other, more complex tasks 2. Reducing monotonous, repetitive queries to improve employee experience 3. Catering to customer preferences – choose quick automated service or deeper human engagement 4. Reducing queue times, in turn improving customer experience 5. Lessening the opportunity for human error 6. Generating ROI by reducing staff numbers These results almost identically mirror the benefits that intelligent chatbots can provide customer service teams. By implementing a bot, a large portion of frontline support can be automatically managed by the bot which: 1. Gives agents more time to handle complex questions 2. Reduces the monotony of answering repetitive questions 3. Allows customer to choose between chatting to a bot or an agent 4. Reduces wait time and queue length (through bot’s ability to handle infinite simultaneous conversations), in turn improving customer satisfaction through quicker resolution 5. Eliminates human error in data entry 6. Generates substantial ROI through lower service costs See how closely those benefits match? Recommended reading: Chatbot ROI Calculator Why chatbots need humans The relationship between bots and humans isn’t a one-way street. While agents need bots to provide more effective and efficient support, bots need agents to provide the personal, ‘human’ touch that many situations call for. In our latest 2020 Live Chat Benchmark Report, we found that chatbots handle 68.9% of their chats from start to finish – although an impressive stat, it still shows that many queries require an agent’s touch. Recommended reading – 2020 Live Chat Benchmark Report There are always going to be situations that call for human assistance: canceling a subscription, reporting a lost or stolen credit card, or registering a serious complaint. Or maybe the topic is sensitive, and your customer would feel more comfortable explaining their situation to an agent. Similarly, some (though increasingly less: stat?) people are still wary or reluctant to communicate with bots and prefer to only speak with a live agent. To cater to these customer preferences, it’s vital that these customers can be routed past or transferred from your chatbot to human agent without effort and without having to repeat themselves. It’s important to note however, that transferring from bot to agent isn’t always just in the interest of the customer – it can often benefit the customer service team too. This is because not all queries are equal. For example, if a customer reaches out asking about a bank’s opening times, this can be easily managed by a bot. However, when the same customer asks about a loan, this high-value interaction may dictate that – according to your unique customer service view – a human agent takes over immediately to ensure the customer receives the best experience and you close the deal as quickly and effortlessly as possible. If your chatbot can’t do this, turn it off and find a chatbot that can (we can help with that). How to create the perfect chatbot – human (agent) balance To begin creating the right balance between chatbot and human, you need a bot that’s widely accessible to today’s digital-first consumers; your bot needs to be where they are, wherever they are. Comm100’s AI Chatbot can serve customers on web, in-app, Facebook, Twitter, WeChat, WhatsApp for Business, and SMS. You also don’t need to build separate chatbots for each channel. Simply select the channels you want your bot to be available on (hint: all of them!) and you’re off. Although your customers will know they are speaking to a bot (and you should make this clear to them to set expectations), you need a bot that understands natural human language. Comm100’s AI Chatbot harnesses the world’s most advanced NLP engine so that it can understand your customers’ goals and provide the answers they’re looking for. Better still, add a large range of off-the-shelf integrations to this, and the Comm100 bot can begin performing actions on behalf of your customers – from tracking an order and paying a bill, to booking a flight. By resolving a large portion of your frontline customer service questions, your agents will have more time to focus on higher-value queries and customers that matter most to your bottom line. Recommending reading: Comm100 Chatbot Resolves 91% of Assigned Live Chats for Tangerine As we’ve discussed earlier, there will be times when you or a customer would rather connect with an agent than a bot. It’s crucial that your bot offers this flexibility. Firstly, your bot should be able to give the customer the option to speak to an agent at any time. Eighty-six percent of consumers believe they should always have the option to transfer to a live agent when dealing with a chatbot. You can easily set this option up within the Comm100 AI Chatbot. Next, you need a bot that can automatically identify the conversations that you want an agent to manage. This requires training your bot on the topics – ‘intents’, in bot lingo – that your customers will bring up. If there are specific intents that are of high value to you, you can tag them so when a customer mentions it, the bot recognizes it and automatically transfers the chat to the appropriate agent or department. The bot can also be trained to notify an agent or escalate the conversation when asked a question it can’t answer or if a visitor is clearly frustrated. As a failsafe, your agents should also be able to monitor bot conversations and take them over in these situations. Wrap-up Chatbots will never replace whole customer service teams, and nor should they. The ‘human touch’ is still essential to customer support, and we are a long way off until this changes. However, if implemented intelligently, bots can resolve a great portion of customer queries without any human involvement, allowing team sizes to reduce, or remain the same in the face of increased support volume. Take Tangerine, an Australian telecom company, for example. They experienced rapid growth, which in turn produced a surge in chat requests. By implementing Comm100’s AI Chatbot, up to 91% of assigned live chats were resolved by the bot without any agent involvement. As a result, Tangerine could manage the increase in chat volume without hiring and training more agents. And when high-value customers reached out, their agents were free to provide them with the best experience.

Read More

How safe is our quantum future?

Article | June 28, 2021

If you're my age, you will remember the critical premise of the 1992 classic "Sneakers" premise, starring Robert Redford and Ben Kingsley - a top-secret black box that can break the encryption of any computer system. Quantum computing is that "black box." In the next 2-7 years, quantum computers could change the face of cybersecurity. Once they can factor products of large prime numbers (the basis of current cryptography) (expected between 2024 and 2030) – existing cyber-defense mechanisms will be rendered obsolete. We need to plan for encryption in the quantum future. What is Quantum Computing? Classical computers use binary arithmetic - all numbers are a sequence of bits - either a 1 or a 0. However, a quantum bit (qubit) exists not as a 0 or 1 but as a superposition of the two (think Schrödinger's cat). Every additional qubit doubles the processing power of a quantum computer, allowing it to execute multiple computational paths simultaneously. Similarly, as per Grover’s algorithm, it is a known fact that quantum computing divides the key space of symmetric cryptography algorithms by two, meaning that their key sizes have to be doubled to keep the safety margin of today. In October 2019, Google demonstrated quantum supremacy with Sycamore. It performed a series of operations in 200 seconds that Google claimed would take a supercomputer about 10,000 years to complete. In December 2020, physicists from the University of Science and Technology of China in Shanghai performed a Gaussian boson sampling technique with their photon-based quantum computer, named Jiuzhang. They declared that Sunway TaihuLight (the fourth fastest supercomputer in the world) would require 2.5 billion years (approx. half the age of the Earth) to finish the computations done by their quantum computer in a mere 200 seconds. Cryptography: The gatekeepers of security As the wise Spider-Man said – "With great power comes great responsibility. And great risk.” Much of the world's encrypted data is protected using mathematical equations with millions of reasonable solutions. These encryption models are too complicated for even supercomputers to solve within an acceptable period, which quantum systems can quickly solve. Modern cryptography relies on symmetric and asymmetric standards. The significant difference is that symmetric cryptography is based on substitution and permutation (there is no underlying mathematical assumption) and uses a single key for encryption and decryption. In contrast, asymmetric key / public key cryptography uses two different keys for encryption and decryption. Since the mid-90s, researchers have theorized that quantum computers can break current public-key cryptographic (PKC) systems. Their ability to concurrently test multiple hypotheses (using Shor's factorization OR Grover's exhaustive search) at unprecedented speeds will make both asymmetric and symmetric cryptosystems redundant. Understanding 5G 5G is one of the most eagerly awaited technologies in the digital world, and with good reason. In the years ahead, 5G coupled with IoT, could revolutionize the integration of digital and physical worlds. What sets it apart from its predecessor? 5G speed - it is nearly 20x faster than 4G. An average-length movie takes 6 minutes to download on 4G and less than 20 seconds on 5G. 5G supports 10x more devices per sq. km. It will seamlessly handle many more devices within the same area – a boost for IoT infrastructure. 5G latency is 25x less than 4G. According to McKinsey, 5G will speed up the mainstream adoption of IoT across multiple industries: Transport, Manufacturing, Healthcare, to name a few. 5G and Quantum – the Perfect Storm While quantum systems provide the compute, 5G provides the channel to connect more than just mobile networks (self-driving cars, personal medical tech), thus expanding the 'threat surface.' In a 5G world, secured communications are a critical component of connectivity, and post-quantum cryptography will play a key role. Researchers globally are devising ways to embed quantum-safe cryptography into 5G networks without compromising QoS. I even came across a patent for a quantum-resistant 5G SIM card by a Swiss company that set an industry best practice in ITU-T X.1811 for quantum-safe 5G. Cryptocurrency Wallets: A prime candidate for Quantum hacking Imagine you forget the password of your Bitcoin wallet, which in theory had millions of dollars in the balance. With a quantum computer, you could unlock your wallet and save yourself many worries, which worries all cryptographers. If malicious players had a quantum computer, the first thing they would try and break is the Elliptic Curve digital signature algorithm, reverse-engineer your private key, forge your digital signature, and subsequently empty your wallet. Thankfully, we are still years away from that scenario, yet that is a telling tale for designing national digital currencies that are supposed to withstand the test of time. Likewise, this vital subject – including applications with legal consequences such as smart contracts enabled by blockchain technologies, which share the same technical basis and, therefore, vulnerabilities to quantum IT -, would need a dedicated article, hopefully soon as time enables it! The real question is: when will quantum computers become a threat to public-key cryptography? As of December 2020, IBM claims to have a 65 qubit quantum computer and already delivering a 53-qubit model to a client (it would take around 1500 qubits to hack Bitcoin private keys). Quantum computers could achieve the required processing power range from as soon as 2024 to as far as 2040 per estimate. How do we solve it? Public Key Cryptography enables over 4.5 billion users to securely access over 200 million websites and engage in over $3 trillion of e-commerce transactions. Further, an estimated 20% of all IT applications rely on PKC and an even higher percentage on symmetric cryptography. According to Prof. Davor Pavuna of the École Polytechnique Fédérale de Lausanne, "several quantum prototypes might already become functional in 2023 (specifically in China)," and that potentially poses a severe protection challenge much earlier!" Many companies are developing "post-quantum cryptography" (PQC) or "quantum-safe cryptography" (QSC) – algorithms whose security is not degraded by any known quantum computing algorithms. Typical ones are McEliece cryptosystem, Lattice-based cryptosystems, Code-based Cryptography, and Hash-based cryptography. While these developments promise 'quantum resistance,' they only reflect our current knowledge of quantum computing capabilities and have a relatively low benchmark set for their security. These methods aim to create mathematical problems that are too difficult for even a quantum computer to solve, with the US National Institute of Standards and Technology (NIST) planning to recommend a PQC standard by 2022-23 and already having done so specifically for hash-based signatures. Similarly, German BSI issued official guidance for using post-quantum key exchange mechanisms, somewhat differing from NIST, and the IETF standardized two hash-based signature schemes, LMS and XMSS, independently, also with differences. Last but not least, the ITU-T issued without much publicity an amended recommendation on IPTV security X.1197 Amd1 that provides comprehensive guidance on state-of-the-art standard PQC options available as of late 2019, for use in multimedia transmission, with a corrigendum issued in early 2020. Applying the Solution Post Quantum cryptography is a developing field. Although these algorithms are quantum-resistant in theory, there is an unpredictability about their efficacy. Secondly, these algorithms are heavy on memory and compute requirements, making it challenging to apply them universally. On the other hand, symmetric cryptography is more efficient and shows more resilience to quantum IT, yet needs an upgrade to accommodate larger key sizes. One such system I came across was a patent of the aforementioned Swiss company is eAES®, which enhances AES’s quantum resistance. It makes safely increasing the key size a reality (as per NIST’s IR 8105 guidance), a claim confirmed in a report by their competitor Kudelski Security on the former’s implementation for Intel® processors. The transition to PQC standards requires a staged approach. To successfully navigate the impending cryptographic change, companies and governments must embrace crypto-agility - the ability to rapidly adapt and switch between multiple cryptographic standards at varying levels. We must support algorithms from different standardization bodies such as NIST, ETSI, the ITU-T, ISO/IEC, and the IEEE in a connected world with fractured standards. Building a global quantum security alliance We are just laying the foundations of this new security ecosystem; however, more work is needed to drive broader adoption. While the academic, innovation labs, and specialist technical communities are making some progress, cha

Read More

AI: Finding the Fraud Needle in the Big Data Haystack

Article | February 24, 2020

With fraud losses accounting for about 3% of the nation’s overall health care spending each year, pharmacy benefit management firms would be wise to seize the opportunity to battle endemic fraud, waste, and abuse (FWA). The upside can be significant, according to the National Health Care Anti-Fraud Association, which estimates annual losses at $68 billion nationally. While the savings are potentially huge, identifying instances of FWA hiding in the massive data volumes generated by prescribing, dispensing, and covering medicines is no easy feat.

Read More

How Artificial Intelligence Is Transforming Businesses

Article | February 12, 2020

Whilst there are many people that associate AI with sci-fi novels and films, its reputation as an antagonist to fictional dystopic worlds is now becoming a thing of the past, as the technology becomes more and more integrated into our everyday lives. AI technologies have become increasingly more present in our daily lives, not just with Alexa’s in the home, but also throughout businesses everywhere, disrupting a variety of different industries with often tremendous results. The technology has helped to streamline even the most mundane of tasks whilst having a breath-taking impact on a company’s efficiency and productivity

Read More

Spotlight

Teralytics

The better we understand the way we move, the better we can build cities, mobility services and transportation systems to meet our needs. Teralytics offers the most advanced insights on human mobility based on cutting edge data science, proprietary machine learning algorithms and deep technology, capturing billions of signals every day from cell towers and other unique sources. We work with leading telecom companies and data partners around the globe to capture information about people’s geographical locations, movement habits and demographics; all completely anonymized and aggregated.

Events