Vahan&#x27;s AI-Driven virtual assistant helps field sales teams and frontliners do better work at scale.

Vahan - Crunchbase Company Profile & Funding

Vahan&#x27;s AI-based chatbot - Vahan allows employers to hire blue &amp; grey collar workers in large volumes in a number of industries across India

Helping Businesses Hire Blue & Grey Collar Workers Using AI

Additionally, with e-commerce and ... from Columbia University before moving to Bangalore, founded Vahan, a startup that is attempting to help these companies find potential blue-collar workers at scale....

Y Combinator-backed Vahan is helping low-skilled workers in India ...

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Madhav Krishna - Founder & CEO - Vahan

At Vahan, we’re helping 300M+ low-skilled workers in India find jobs using WhatsApp. We’re a Y Combinator company that is backed by marquee investors such as Khosla Ventures and Founders Fund; several executives from Google and Flipkart are also investors in the company.

Vahan | AngelList

Dun &amp; Bradstreet helps companies improve their business performance through data and insights delivered through our Data Cloud and Live Business Identity

Vahan Karaoghlanian Company Profile | Burbank, CA - Dun ...

Vahan Trucking, Inc. is a licensed and DOT registred trucking company running freight hauling business from Norco, California. Vahan Trucking, Inc. USDOT number is 419186. Vahan Trucking, Inc. is motor carrier providing freight transportation services and hauling cargo.

Vahan Trucking, Inc. USDOT 419186 - Norco, California Trucking Company

I run a company called Vahan (Khosla Ventures backed) where we’re building India’s largest labor marketplace for the gig-economy. I have a Masters in Artificial Intelligence from Columbia University.

Vahan: Building a labor marketplace for the gig-economy in India ...

Stylish, sophisticated, and comfortable luxury jewelry for women. Established in 1968, VAHAN is an awarding winning designer of gold, sterling silver and diamond jewelry.

VAHAN Jewelry | Gold, Sterling Silver & Diamond Designer Jewelry

VAHAN 4~152~9

Vahan, an Armenian who had been the garrison commander of Emesa and served as magister militum per Orientem during the Byzantine–Sasanian War of 602–628, was the overall field commander at the Yarmuk. While Vahan and part of his forces avoided destruction in the battle itself, they were ...

Vahan (Byzantine commander) - Wikipedia

Look up vahan in Wiktionary, the free dictionary.

Vahan - Wikipedia

The VAHAN is an assault rifle of Soviet/Armenian origin and was designed by Engineer and Firearms Designer Vahan S. Manasian. It can be fitted with a GP-30 grenade launcher, bayonet and scope. The weapon dates back to 1952 as the MBC-2 prototype when Manasian was a soldier in the Soviet Army.

VAHAN (firearm) - Wikipedia

|| V A H A N | National Register e-Services | Ministry of Road ...

Various services related to new/old driving licence or learner&#x27;s licence like Appointment Booking, Duplicate driving licence, Application Status, Online test for learner&#x27;s licence, etc · Drivers/ Learners License

Home | Parivahan Sewa | Ministry of Road Transport ...

Vahan joined NREL in October 1994 and has served many roles over the years. He is currently serving as Chief Engineer at NREL’s Power Systems Engineering Center and as an IEEE Fellow. His contributions to NREL research have been recognized through the NREL Hubbard award and multiple Outstanding ...

Vahan Gevorgian | NREL

Explore VAHAN&#x27;s renowned collection of stackable bracelets.

Jewelry for Women: Bracelets, Earring, Rings, Necklaces, & Pendants ...

Starting from hand-drawn sketches, each piece of jewelry is designed and produced in the USA. VAHAN was founded in 1968 by classically trained French Designer Sacha Der Calousdian. From a modest, one man, Manhattan based studio, Sacha has grown the company into a leading American made, family ...

Vahan by Alwand Vahan – Embler's Jewelers

Vahan : Vehicle Registration/Fitness/Tax/Permit/Fancy, Dealer helpdesk-vahan[at]gov[dot]in, +91-120-2459168 6:00 AM-10:00 PM

വിദ്യാവാഹന്‍ ആപ് | Motor Vehicle ...

VAHAN 4.0 (Citizen Services) ~onlineapp01~135~8014

Vahan is a technology company headquartered in Bangalore. We help companies such as Zomato, Swiggy, Flipkart, Uber, Shadowfax etc. hire blue-collar workers and are on track to become India's largest recruitment platform. We are backed by an illustrious set of investors such as Y Combinator, Khosla Ventures, Founders Fund and Airtel.

Vahan

Elon Musk’s Next Logical Move — Electric Airplanes — Modular Strategies for Sustainable Global Mobility In Australia, Elon Musk built an electric battery plant that can back up the grid within milliseconds. And he’s losing money with it. Tesla’s 100 MW/129MWh system near Jamestown, Australia provides backup power for South Australia’s energy grid. because the grid only measures electricity pumped into the system a full 6 seconds after a breakdown event. Powerpack 30–40% of the electricity it provides goes unpaid The Powerpack farm responds in milliseconds: 0.14 seconds the last time it had to back up the grid. Why lose money instead of adding in an artificial 6 second delay? Because Elon Musk’s next project is beautiful. But it’s not about airplanes. Next project: Provide a huge number of low income households with electric batterypacks, and due to the very low latency, connect them over some distance (it’s likely they would be in the same area) into a mega-plant. A plant much larger than the Jamestown Powerpack, which is already the largest in the world, and already essential to Australia’s electric grid. South Australia’s premier Steven Marshall has already voiced opinions against the 250 MW/650 MWh virtual power plant, which would unite 50,000 low-income residential units outfitted with Powerwall 2 systems. The project, however, is brilliant. You give low-income households not just energy independence, but a means to generate income while stabilizing the electric grid of an entire country, nay, continent, and you create a modular and scalable pathway to global energy independence. Musk’s company would likely act as a legal intermediary between individual households and the grid, and would also likely take a percentage, but the rest would go to low-income individuals as much needed financial stability. A background buzz of solar paychecks slowly but surely trickling into disadvantaged areas. Beautiful. And once the project itself is completed, it becomes proof of concept for a much better kind of battery array. One that doesn’t need to be out in the desert. It can be implemented anywhere, and all of a sudden suburbia becomes low-latency solar heaven, and low-income areas globally become the world’s electricity producers at the speed that battery packs can be manufactured. But this is just the first half of the plan. The second half is much better. From a small business, entreperenurial and especially social enterprise and collaborative production point of view, . once low-income neighborhoods are net energy producers, they can organize, cooperate and collaborate in countless other ways Further technology investments can be made at much lower costs, because there is a local and independent electricity grid to support them, which leads to development, local production and especially peer production and cultural development, and even local trade. I’m not going to go too deep down the path of what is possible there, but it opens up all sorts of avenues at the level of inter-community projects and development over larger areas. With the electricity costs for 3D printing covered, . The only thing left to do is for someone to invest in a technological pathway for bioplastics instead of biodesel, and . local production of goods in a globally distributed knowledge-ecosystem becomes possible both 3D printing and solar electricity become self-replicating with a production cost of zero But that’s another story. Back to the future of airplanes now. Musk is already working on cars, rockets and underground transportation. That covers all modes of travel except for planetary flight. If you have the technology for space travel, you can engineer your way to airplanes. And in this case, there are intermediary steps. Flying cars are a few years away, and self-driving cars are more or less already happening. Both will require AI, and Tesla already has the niche learning cycles for self-driving. Musk’s deep learning company, OpenAI, is developing AI in the general sense — the sense that, when mature enough, allows you to take deep learning and apply it to any niche. Such as going from self-driving cars to self-flying cars, which I wager is a simpler technology, and in terms of physics, easier to handle than landing the Falcon Heavy after atmospheric re-entry. Flying cars are a step up towards general flight, but they still require individual ownership, or rental in urban areas. Planetary flight as a factor of sustainable global mobility requires two things: a sustainable global battery array for solar, and electric commercial airplanes. The airline industry predicts . 10 years until commercial airliners could go fully electric The big performance hiccup is battery power. Tesla’s home field. US-based startup Wright Electric is . Every other electric plane being designed has much smaller capacity, with Boeing’s 12 passenger plane produced by Seattle startup Zunum Aero being the most spacious. NASA, too, is in the game, with its X-57 two-seater. working to create a 120–186 seat electric aircraft with a 335 mile range Airbus Vahana Airbus has two projects, the Vahana (single seat) and the CityAirbus (four seats), both self-piloted and both meant for urban use. Vertical take-off, obstacle avoidance and complex navigation: when coupled with low operating costs, Airbus plans on competing with taxis in urban spaces. I’m going to cut to the chase. The world is obviously moving towards electric airliners. If you Google it, you can feel the trend. Green, low-noise, friendlier near or within cities, it’s a huge business move. And the only company with the battery tech to actually lead in this space is Tesla. It’s not just the technology onboard the airplane, it’s the whole ecosystem. How you charge planes, where the energy for charging comes from, and how it is stored. Tesla has the end to end technology to pull it off and do it sustainabily, which is the key metric for marketing this in the future. If the airplane is electric, but the electricity used to charge it is not sustainable, you haven’t really pulled off sustainable flight. Tesla’s infrastructure would be not just sustainable, but grid-independent. Once Tesla has the modular global battery array it’s aiming to build, with individual home units connected into giant virtual power plants, the next logical move are electric airplanes. If you had to bet, would you say Elon Musk is aware of this? He probably has been for a while. It would be a natural offshoot of SpaceX. And once Tesla has commercial electric flight, it no longer needs to monetize electricity by relying on the antiquated power grid. In fact, even running battery plants like the one in South Australia at a loss, and building as many of them as possible as fast as possible would be a winning move. Building the momentum and political cred to obtain various form of investments and subsidies for turning entire low-income areas into net energy producers and instant-acting, smart virtual power plants. Then change the whole game by adding a different layer of monetization and technology. They would turn low-income neighborhoods into dynamic equity holders in global mobility. And make zero-emissions global mobility possible. The gains in prosperity and collaborative potential for the species, on a global scale, starting with otherwise segregated low-income communities would be immense. At some point in the process, self-flying commercial planes and an AI flight grid for both self-flying cars and planes becomes the status quo, but that’s another story. There’s a lot of ‘other stories’ here. Such as, Musk is looking to upend the electricity storage and production monetization scheme anyway, regardless of electric commercial flight. It’s essential for Tesla’s lifestyle proposition — turning electricity charging for Tesla cars from reliable and financially sound into limitless and abundant. The power grid runs what? Homes and transportation mostly, from a consumer standpoint. In a more general sense: businesses, civic infrastructure, social entertainment and social services. Tesla is connecting the consumer part, homes and transportation interlinked in one electric continuum. Into a self-assembling modular mesh of independent and smart electricity generation and storage units. Once it’s done that, it has its own economy, and right now, it’s approaching this equation from all sides. Providing perfect solutions on the consumer end, innovating and providing services in a globally-scalable manner on the power grid end. There is not one piece of the puzzle for electric commercial flight that isn’t already moving in place for Tesla. And there is not a single company that is anywhere close to having as many pieces aligned, not Airbus, not NASA, not Boeing, and none of the startups entering the playing field. It’s the perfect power move.

Elon Musk’s Next Logical Move — Electric Airplanes — Modular Strategies for Sustainable Global…

RideSharing is the economic powerhouse driving autonomous vehicles to take flight. Lyft’s self driving car and Lilium Jet The RideSharing model changed everything we knew about mobility. Packed metro rides and graffiti covered busses transformed for many into hailing a cab. As the driver begins to become less important, and billions of dollars go into autonomous systems, the car itself is evolving. Many people today talk about how the end goal is self driving cars, but the technology will quickly surpass self driving and take flight. Lulium Jet I sat at the Launch of Ola Play in Bangalore, India. I was the only foreigner, half crazed and sleep deprived. Ola had just announced the first in-car computing platform custom designed for RideSharing. With only an hours sleep, I watched history unfold before me. “To date, to be very honest,” Amit Sagar, of Mahindra explained, “Every single innovation has been focused towards the driver. But now the time has come to focus our attention on the passenger sitting in the rear seat.” For the first time in history, an automaker stated publicly that the passenger was becoming more important than the driver. The VP sales continued in Jobsian fashion, “We are at an inflection point, and with this we will lead a new story going forward.” Mahindra, one of India’s largest automakers, had just revealed that vehicle design is changing forever, with focus now shifting to the passenger. In countries like India, most of the population will never own a car. DARPA Funded has partnered with Uber (Aurora) Aurora In the past, flying cars were expensive dreams. It would be prohibitively expensive to have flying cars until a new economic model arose, RideSharing. The RideSharing model meant that one vehicle could have many trips, operating at near maximum efficiency. This means that the cost of the vehicle can be distributed across thousands of rides. RideSharing enabled mobility for people in India that could never afford a car. This same RideSharing model means that flying cars have just found a way to become affordable for the masses. In fact, Flying cars appear so lucrative, RideSharing companies like Uber and Lyft have been partnering publicly (and through the grapevine) on deploying Vertical Take Off and Landing vehicles (or VTOL, as the industry prefers). Uber released a white-paper in 2016 with astounding numbers. A VTOL trip from San Francisco to San Jose will soon become competitive with a cab ride. Uber Elevate Even more interestingly, because much of the cost associated with operations are human, (maintenance, etc.) VTOL RideSharing will be economically feasible even in places like India: Uber Elevate I have personally ridden in an Ola Cab from Gurgaon to Connaught Place in Delhi (after too much to drink in Cyber City). Rs 1000 (~$15 USD) for a flying car would become extremely popular. Uber is planning tests in Dubai and Dallas, where they held their secretive, Invite only Elevate Conference. Ehang at CES Las Vegas (Author) On the other side of the Earth in China, companies like Ehang are racing ahead on their own. At CES 2017 in Las Vegas, a representative told me that Ehang and Uber were “In Conversation”. In my opinion there is no reason to partner. Whomever owns the autonomous VTOL infrastructure will benefit from its revenues. Handing that off to another company like Uber doesn’t make sense. This idea is validated by the fact that OEMs like Tesla, and Volkswagen have publicly stated their self driving cars will not be allowed on Uber. The RideSharing industry is slowly fragmenting as automakers build their own RideSharing Networks. On the other hand, RideSharing companies like Uber, Lyft, Gett, and Waymo are actively developing their own Autonomous Technologies. Whomever owns the infrastructure, owns the revenues from an autonomous network. Uber and Lyft, by developing their own hardware, are actively preparing themselves for a future of flight. Lilium As technologies surrounding autonomous systems, battery technology, and robotic flight are converging, dozens of companies are building flying cars. The technology exist right now in prototype and in the air. DARPA funded Aurora and German Lilium jet have become top contenders using electric ducted fan motors. Joby, Kitty hawk, and Zee.Aero are all coming out of Silicon Valley, building working prototypes (the latter two are funded directly by Google’s Larry Page.) Governments and Venture capitalists are pouring money into VTOL. While most VTOL startups are still in“stealth”, according to Crunchbase, Lilium alone has raised over $101.4 Million USD. Massive funding in autonomous vehicle hardware and software is further lowering the cost of deploying VTOL infrastructure. Computer vision software, and robotic hardware are converging so quickly that even the big, slow moving aerospace companies are getting involved. AirBus has spun off two projects, Pop.up and Vahana. Vahana, in ancient Sanskrit means “one that carries” appearing in the Bhagavad Gita thousands of years ago. The ancients believed in flying cars, now investors do too. AirBus Vahana Money, technology, and demand exists right now to make flying cars economically feasible. What we are waiting for is legislation. Existing Ride Sharing companies already have a foot in rapidly developing countries’ legal systems (RideSharing is still illegal in most places, but governments turn a blind eye.) Uber has even been accused of bribery. (Wall Street Journal Via Engadget) As more “developed” countries await legislation around licensing autonomous flight, places like Dubai and China are pushing forward with live tests. It is not difficult to imagine that in the next 3 years, VTOL RideSharing will be very real in many places. Unintended Consequences The consequences of autonomous flight will also be very real. Many claim that autonomous cars alone may drastically reduce property value in cities ( ). Curbed explains that developers like AvalonBay in Los Angeles are already designing for an autonomous future. As self driving cars reduce the need for parking garages, AvalonBay is designing their garages to be converted into housing. Curbed has done a great article on this While autonomous cars may help developers maximize urban space, VTOL could accelerate de-urbanization for those who can afford it. If VTOL can expand in cost and access faster than city populations can grow, property may begin to devalue as the ultra-rich move away from city center. Autonomous systems are going to fundamentally change the way our cities are designed. Lilium Why would anyone live in the city, if they could bypass the chaos of traffic and live somewhere more affordable? Lilium estimated their VTOL jet will put much of Marin County (North of San Francisco) Into range of downtown. It is not difficult to imagine climbing to the roof of your Marin County home, awaiting a VTOL to San Francisco. Your Apple watch pings, and a shining electric VTOL settles onto your solar landing pad. The electric Vahana or Lilium jet takes off and lands in SoMa ten minutes later. If Uber’s Elevate white paper is accurate, it may not only be more affordable, but faster to commute from somewhere like Marin, than to take a cab through Silicon Valley. VTOL could drastically enhance the value of land around our cities, and make center city “uncool” to live. Deurbanization VTOL Oasis (Author) In the 1920’s, when airplane ranges were still small, futurists imagined giant floating islands built at sea, facilitating “hops” across the Atlantic. As the range of VTOL increases, we can begin to imagine flying VTOL instead of a commercial airline. A trip between Los Angeles and Las Vegas could be cut in half by VTOL “oasis” hidden amongst the Sierra Nevada Mountains. We can begin to imagine these new cities arising in the middle of nowhere, strategically positioned between points of interest. The drive for humans to escape cities, and the affordability of VTOL just might replace the Jet age. As new RideSharing models quickly prove feasibility, investors and startups are racing for what lies beyond self driving cars. If legislation can keep pace with technology, our skies, and cities will quickly transform into something new. As technology continues to accelerate at the exponential pace in which we are experiencing, VTOL may quickly evolve into affordable access to outer space. Garrett Kinsman Writes for Autonomous Tomorrow based out of Bangalore, India, and San Francisco. Resources: https://www.uber.com/elevate.pdf _Aurora Flight Sciences is a leader in the development and manufacturing of advanced unmanned systems and aerospace…_www.aurora.aero Aurora Flight Sciences - Apply autonomy and robotics to the development, production, and operation… _Lilium enables you to travel 5 times faster than a car by introducing the world's first all-electric vertical take-off…_lilium.com Lilium

RideSharing means Flying Cars are Here to Stay

Solving the stablecoin dilemma is paramount to crypto’s survival and success as our industry matures. Without a secure, capitally efficient, and decentralized stablecoin, it will be extremely difficult to onboard institutional and retail capital. What are stablecoins? Stablecoins are cryptocurrencies designed to maintain a peg with another currency, asset, or financial instrument. They are most commonly used as decentralized analogs to FIAT currencies, such as USD, EUR, and GBP. This provides traders a more “stable” alternative to historically volatile assets like ETH and BTC. What is the history of stablecoins? were introduced in 2014 by BitUSD (BITUSD) and NuBits (USNBT) and they were collateralized using different baskets of cryptocurrencies. While both of these tokens were revolutionary during their time, neither have managed to succeed at the one key task they were created to carry out, to maintain a “stable” peg with the US dollar. Both stablecoins have since lost their pegs and all but faded into oblivion, but their hurdles and trajectories would foreshadow one of crypto’s biggest unsolved problems, . The first stablecoins “The Stablecoin Trilemma” The Stablecoin Trilemma dictates that no one stablecoin can satisfy all 3 conditions: Price/Peg Stability - ie. The ability to constantly be traded at 1 USD. Capital Efficiency - ie. Having to lock up ≤ 1 USD to mint 1 USD stablecoin. Decentralization - Not relying on centralized custodians to manage collateral. What are the different types of stablecoin implementations? This stablecoin implementation problem has been tackled by crypto’s best and brightest to widely varying degrees of success, however, a perfect solution has yet to be found. As such, there are multiple different implementation strategies, each with its own unique tradeoffs. Broadly, these strategies can be split into two main categories, collateralized stablecoins and algorithmic (aka. uncollateralized) stablecoins. Collateralized Stablecoins A collateralized stablecoin is any cryptocurrency that is either partially or completely backed by collateral held in a treasury or reserve. This backing helps to ensure that the value of a collateralized stablecoin does not fall below its peg. Using USDC as an example, if 1 USDC was traded below 1 USD in value, traders would arbitrage the difference by purchasing USDC and redeeming it for 1 USD each. The inherent issue with FIAT collateralized stablecoins is the centralized nature of the collateral reserves. This opens up token holders to institutional risks like bankruptcy or mismanagement of funds. Collateralized backings are not limited to FIAT currencies alone. As it stands, there are stablecoins such as DAI and sUSD which are collateralized with other cryptocurrencies (namely, ETH and SNX respectively). These stablecoins can mitigate the centralized risk factors associated with FIAT-backed stables, however, due to the inherent volatility of most crypto assets, they require over-collateralized positions (ie 4:1 for USD) in order to maintain their pegs. This system is significantly safer but also much more capitally inefficient for end users. Algorithmic Stablecoins Algorithmic stablecoins are assets that do not rely on collateral reserves to maintain their peg. Instead, they utilize smart contracts to buy, sell, or burn tokens to respond to market supply and demand. In essence, algorithmic stablecoins maintain their pegs by mechanistically controlling their circulating supplies. Examples of algorithmic stablecoins include $FRAX and $UXD. Algorithmic stablecoins are inherently decentralized and fairly capitally efficient, however, their pegging mechanisms have greater sensitivity to extreme market conditions and attacks. $FRAX operates under a fractionally collateralized system, where each $FRAX is partially collateralized by fiat-backed stablecoins and partially backed by its own token, $FXS. The Frax collateralization ratio determines the ratio between collateral (ie. USDC) and algorithm ($FXS) that makes up the $1 FRAX value. An important requirement for $FRAX to function smoothly is to have deep liquidity with other stablecoins (ie. USDC and USDT). The FRAX+3Crv Pool on Curve Finance has nearly 1.1b USD of liquidity to help ensure as little slippage as possible when making trades. $UXD is a “delta-neutral” stablecoin that works by taking deposits, such as $ETH, and using those deposits as collateral to short an equivalent amount of perpetual swap contracts or dated futures. This balanced pair of the $ETH long and 1x ETH-USD short creates a delta neutral position with a value of $1 for each $UXD. If the price of $UXD < $1, arbitrageurs can redeem their $UXD for $1 of collateral assets (currently limited to ETH, BTC, and SOL) to make a profit. Conversely, if the price of $UXD > $1, arbitrageurs can mint $UXD at a cost of $1 per $UXD to make a profit. This mechanism allows UXD to consistently maintain its peg. Currently, $UXD and $FRAX seem to be the front-runners for solutions to the as they are fully decentralized and capital-efficient. What remains is for them to continue to prove their stability over time. stablecoin dilemma Why are stablecoins important/necessary? The vision is simple: Decentralized finance requires decentralized currencies. As crypto is still an emerging market, volatility is to be expected and perhaps even welcomed. However, there must exist an on-chain alternative to “stable” FIAT currencies to act as trading pairs on DEXs and as a means to store capital long-term. About Dan Edlebeck Dan is a co-founder of Sei Network. Active in the Cosmos ecosystem, Dan led Sentinel for the past 2 years. Over the past five years, Dan has held several roles within crypto organizations including leading marketing for Blockparty and operating a PR agency, deedle connects. He is a strong advocate for the power of an inclusive financial system built on web3 infrastructure. About Sei Network is the first orderbook-specific L1 blockchain. It is built using the Cosmos SDK and Tendermint core and features a built-in central limit orderbook (CLOB) module. Decentralized applications building on Sei can build on top of the CLOB, and other Cosmos-based blockchains can leverage Sei's CLOB as a shared liquidity hub and create markets for any asset. Designed with developers and users in mind, Sei serves as the infrastructure and shared liquidity hub for the next generation of DeFi. Apps can easily plug-and-play to trade on Sei orderbook infrastructure and access pooled liquidity from other apps. To prioritize developer experience, Sei Network has integrated the wasmd module to support CosmWasm. Sei Network By Dan Edlebeck Sei Network’s

Crypto’s Stablecoin Throne is Vacant

What's your background, and what are you working on? I’m Satyam Vaghani, Senior Vice President and General Manager of IoT and AI at Nutanix. I joined Nutanix in 2016, when they acquired PernixData, a storage virtualization software company that I co-founded and served as CTO. I started my career as an early engineer at VMware and went on to become Principal Engineer and Storage CTO. I have a Master’s degree in computer science from Stanford and a Bachelor’s degree in computer science from Birla Institute of Technology and Science, Pilani. At Nutanix, I lead product and business for an edge computing stack and IoT application platform that enables people to build and operate new-generation, AI-based IoT apps across planet-scale edge infrastructure. We’ve generated revenue across retail, manufacturing and telecom verticals, and across the world. anix? What motivated you to get started with this IoT initiative at Nut Nutanix is on a mission to make computing invisible everywhere. A key aspect of that mission is to be on the lookout for major shifts in where computing is deployed and why it is so. Towards the end of 2016, many Nutanix customers made it obvious to us that we will see an explosion in the number, significance, and complexity of computing deployed in the real world -- at the edge -- at airports, hospitals, retail stores, factories, oil rigs, autonomous cars and drones, close to 5G base stations, and so on. Analyst reports concluded the same -- that by 2020, we could potentially see 3 orders of magnitude more devices and 40 times more data being created at the edge than all the public and private clouds of the world combined. This was an interesting problem to solve for many reasons… For one, nobody has solved it (although many people are trying). We like such broad, category-creating challenges. We’ve done it once already back when Nutanix was founded. We made and then led the market for hyperconverged infrastructure. While that business chugs along, it is time to build something spectacular again. Secondly, the edge is a major shift in compute paradigm. Computers in public and private data centers often serve “human-oriented” use cases -- we care about email, working on spreadsheets (yeah, right!), surfing the web, and social media and so on. Computers on the edge most-often serve “machine-oriented” use cases -- the edge at a factory processes real-time machine telemetry data to further optimize those machines, and so on. The operating system and services for machine-oriented computing, and distributed across 100s or 1000s of edges has to be fundamentally different from the operating system for humans. This is an interesting design problem. Finally, we often marvel at the grandeur of computer systems we have created so far. Now, imagine creating computer systems that need to process 40 times more data than all of that. What went into building the initial product? We spent roughly two months researching the market and devising the product strategy, another three months designing the product and the next 15 months creating 1.0 via a series of agile sprints. In parallel, we ran a beta program with the Global 2000 customers across a variety of verticals to validate our approach and patch any unforeseen gaps in product requirements. At the time of shipping 1.0, we had people using it in production. As is typical with these things, we had a very aggressive schedule and we were very tight on staffing. One key learning from the journey was that the product team achieved a much higher level of productivity because they were almost always directly involved in a customer beta and hence felt naturally motivated and clear about our purpose, timelines, and goals. Are there any specific industries you’re focusing on right now? What are some of the most interesting use cases for IoT you have seen? We focus on retail, manufacturing, smart cities and telecom. In retail, customers often tend to leverage us to create new experiences like cashier-less checkout systems. Manufacturing is all about factory automation, predictive maintenance of factory machinery, and automated product quality inspection. Smart cities are an amalgamation of retail and manufacturing design patterns with added complexity layers around privacy, scale, data governance, etc. Finally, telecom is about modernizing the communications edge, and potentially monetizing it in light of upcoming 5G applications. How have you attracted customers and grown the initiative? One clear source of traction is our existing 13,000 odd Nutanix customer base, and more specifically, the 800-900 of Global 2000, government and service provider customers. The Edge, IoT and AI offering is a natural step in their journey with Nutanix as they grow beyond private datacenter based use cases to multi-cloud use cases and workloads incorporating new concepts like micro-services based application architecture and AI-based data processing. What's your business model? I won’t go into details for obvious reasons. But a few things that stand out doing the IoT and Edge business are that there is a marked lack of industry-wide statistics in this space to plan or measure one's success against the industry as a whole. This is not surprising because we are still in the process of making the market. However, it makes revenue and resource planning much harder. The relative nascency of use cases makes product planning much harder too. What are your goals for the future? Unlike a business where one sells CRM software or databases or storage systems, this is a business where the requirements from your product vary highly by vertical. What a retailer needs from this product is dramatically different from what an oil and gas services company needs or automotive manufacturer needs and so on. Our main goal is to understand each of these markets much more deeply so we can tailor our product and business to the market. A related goal is to train our employees to have deep empathy for the “customer-business-downwards” way of relating and selling to our customers, as opposed to the more frequent “vendor-technology-upwards” way. What's your advice for entrepreneurs who are just starting out? There are many things that come to mind, but I’ll share two: One, if this is your first go at entrepreneurship, chances of success are higher if you focus on a product and market that you already know very well. Entrepreneurship has been romanticized around having earth shattering ideas that no one else thought of. But a majority of startups and entrepreneurs are about the disciplined pursuit of a market that they are rightfully good at addressing. Yes, we all marvel at the occasional AirBnB or Slack or Facebook, but one must realize that the chances of that happening are the same as the chances of Tom Brady winning at Wimbledon on his first attempt. Two, don’t do it for the money. The challenge and requirements of the entrepreneurship journey are not to be trivialized. Do it for the stories you want to live to tell, and the people you want to tell them with. Where can we go to learn more? Visit to learn more about Nutanix’s Xi IoT initiative, and to start a free 10-day trial to experience the IoT application development in a cloud environment. www.nutanix.com/products/iot You can also follow Nutanix IoT on . Twitter This interview is brought to you by , a tool to schedule and automatically repeat your posts on Facebook, Instagram, Twitter, Pinterest, LinkedIn, and OneUp Google My Business

Founder Interviews: Satyam Vaghani of Nutanix

How to Find Out If You're Paying for Slow Internet

In today’s fast-paced job market, Staffing agencies are becoming key players in the future of work. This is because as jobs change and new skills are constantly required, traditional hiring methods are rethought. According to the American Staff Association (ASA), nearly three million temporary and contract employees work for America’s staffing companies during an average week. It represents a broad trend toward flexible business processes. This shift is being driven by staffing companies offering innovative solutions that not only meet the immediate needs of staff but also prepare organizations for tomorrow’s challenges. Understanding the Evolving Role of Staffing Agencies Traditionally, they were seen as street saviors who jumped in whenever companies needed to fill vacancies quickly or there was a shortage of temporary workers, and today, their role has changed dramatically. Staffing agencies are now building relationships with companies where they help these organizations anticipate recruitment needs, manage talent pipelines, and staff the changing market dynamics. One of the most important functions of modern personnel agencies is the ability to provide exceptional talent. As technology advances, for example, the demand for specialized roles in AI, cybersecurity, and blockchain has increased. Staffing agencies have revolutionized internationally by expanding their search and recruitment but also by using sophisticated technology to better match the right candidate with the right job. How Staffing Agencies Enhance Workforce Flexibility? The concept of ‘working for life’ is becoming obsolete. Today’s workforce, especially millennials and Gen Z, value work-life balance, flexibility, and the opportunity to work on their own terms. According to the American Staffing Association (ASA), during the course of a year, America’s staffing companies hire over 14.5 million temporary and contract employees. Staffing agencies are facilitating this new employment arrangement by offering contract positions, part-time roles, and temporary work offering flexible staffing and recruitment services for both employers and employees. For businesses, the flexibility offered by staffing companies means they can increase or decrease their staff based on the demands of the business without being burdened with long-term commitments. This flexibility is important, especially in projects and events such as IT, where the scope and timeline of the project can change dramatically. Leveraging Global Talent In a globalized world, geographical boundaries no longer limit talent. Staffing agencies have become important links connecting global talent pools with local and international companies. This globalization is especially useful for areas where specific skills are lacking. By leveraging a broader pool of talent, companies can not only better address skills gaps but also increase diversity within their teams. Teams bring diverse perspectives and tend to be highly innovative and robust in problem-solving, qualities critical to competitive advantage in today’s marketplace. Navigating Regulatory Landscapes Employment laws and regulations can vary greatly from region to region. Working groups help companies navigate these complex legal issues, ensuring compliance and reducing the risk of legal challenges. Whether understanding new labor laws, managing contracts, or enforcing fair labor practices, staffing agencies provide a valuable service that protects both employer and employee. Impact of Technology on Employees Staffing solutions combining artificial intelligence and machine learning are transforming the hiring landscape. This technology simplifies, manages, and automates the recruitment process, as well as recruiters are able to focus more on engaging with prospective clients and understanding the needs of the companies they serve. Conclusion: The Role of Systemart in Shaping a Successful Future As we look to the future, the role of staffing agencies in successful businesses becomes more apparent. Systemart professionals stand out as leaders in the industry, providing tailored solutions that help companies remain agile, competitive, and forward-thinking. With a commitment to innovation and in-depth knowledge of market trends, Systemart is geared to not only help your business meet immediate employee needs but also provide a flexible workforce, and they are active and ready for tomorrow’s challenges. In partnership with Systemart, business In today’s fast-paced job market, staffing agencies are becoming key players in the future of work. In today’s fast-paced job market, Staffing agencies are becoming key players in the future of work. This is because as jobs change and new skills are constantly required, traditional hiring methods are rethought. According to the American Staff Association (ASA), nearly three million temporary and contract employees work for America’s staffing companies during an average week. three million It represents a broad trend toward flexible business processes. This shift is being driven by staffing companies offering innovative solutions that not only meet the immediate needs of staff but also prepare organizations for tomorrow’s challenges. Understanding the Evolving Role of Staffing Agencies Understanding the Evolving Role of Staffing Agencies Traditionally, they were seen as street saviors who jumped in whenever companies needed to fill vacancies quickly or there was a shortage of temporary workers, and today, their role has changed dramatically. Staffing agencies are now building relationships with companies where they help these organizations anticipate recruitment needs, manage talent pipelines, and staff the changing market dynamics. One of the most important functions of modern personnel agencies is the ability to provide exceptional talent. As technology advances, for example, the demand for specialized roles in AI, cybersecurity, and blockchain has increased. Staffing agencies have revolutionized internationally by expanding their search and recruitment but also by using sophisticated technology to better match the right candidate with the right job. How Staffing Agencies Enhance Workforce Flexibility? How Staffing Agencies Enhance Workforce Flexibility? The concept of ‘working for life’ is becoming obsolete. Today’s workforce, especially millennials and Gen Z, value work-life balance, flexibility, and the opportunity to work on their own terms. According to the American Staffing Association (ASA) , during the course of a year, America’s staffing companies hire over 14.5 million temporary and contract employees. American Staffing Association (ASA) 14.5 million Staffing agencies are facilitating this new employment arrangement by offering contract positions, part-time roles, and temporary work offering flexible staffing and recruitment services for both employers and employees. staffing and recruitment services For businesses, the flexibility offered by staffing companies means they can increase or decrease their staff based on the demands of the business without being burdened with long-term commitments. This flexibility is important, especially in projects and events such as IT, where the scope and timeline of the project can change dramatically. Leveraging Global Talent In a globalized world, geographical boundaries no longer limit talent. Staffing agencies have become important links connecting global talent pools with local and international companies. This globalization is especially useful for areas where specific skills are lacking. By leveraging a broader pool of talent, companies can not only better address skills gaps but also increase diversity within their teams. Teams bring diverse perspectives and tend to be highly innovative and robust in problem-solving, qualities critical to competitive advantage in today’s marketplace. Navigating Regulatory Landscapes Employment laws and regulations can vary greatly from region to region. Working groups help companies navigate these complex legal issues, ensuring compliance and reducing the risk of legal challenges. Whether understanding new labor laws, managing contracts, or enforcing fair labor practices, staffing agencies provide a valuable service that protects both employer and employee. Impact of Technology on Employees Staffing solutions combining artificial intelligence and machine learning are transforming the hiring landscape. This technology simplifies, manages, and automates the recruitment process, as well as recruiters are able to focus more on engaging with prospective clients and understanding the needs of the companies they serve. Conclusion: The Role of Systemart in Shaping a Successful Future As we look to the future, the role of staffing agencies in successful businesses becomes more apparent. Systemart professionals stand out as leaders in the industry, providing tailored solutions that help companies remain agile, competitive, and forward-thinking. With a commitment to innovation and in-depth knowledge of market trends, Systemart is geared to not only help your business meet immediate employee needs but also provide a flexible workforce, and they are active and ready for tomorrow’s challenges. In partnership with Systemart, business In today’s fast-paced job market, staffing agencies are becoming key players in the future of work.

The Role of Staffing Agencies: A Game Changer in the Future of Work

স্টাফিং এজেন্সিগুলির ভূমিকা: কাজের ভবিষ্যতের একটি গেম চেঞ্জার৷

Die Rolle von Personalagenturen: Ein Wendepunkt in der Zukunft der Arbeit

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About me and my experience Hi, I'm Alina. With nearly 9 years in design, my journey started much like many of my peers – from graphic and web design to my current role as a product designer. My focus lies in crafting and enhancing user interfaces, conducting tests, gathering components, and ultimately aligning business objectives with exceptional user experiences. Today, I want to share my insights on job hunting, hoping to benefit newcomers and seasoned professionals alike. Why UX/UI? What drew me to this path? Art captivated me from a young age, leading me to explore graphic design despite initially pursuing advertising. Through persistence and learning various design software, I gained entry into the field, starting in small web studios. As I delved deeper, my interest grew, and I expanded my skills through research and hands-on experience in diverse product teams. Now, I'm with Planneer5d, a global leader in interior design technology, serving millions worldwide. While my background in drawing sparked my interest, the UX/UI profession prioritizes engineering prowess over artistic talent. Why write about job hunting? Having navigated the job market myself, I understand the challenges and uncertainties that come with it. I want to share my experiences and insights to help others in the design community find their footing and secure rewarding opportunities in this ever-evolving field. Skill-set of a UX/UI designer in 2024 One of my biggest failings was that I initially entered the UX/UI market without the . And I always tried to research in a new place, either on my own or with the help of a research center, but I always had a great zeal to experience it in practice, to learn how it works. More often than not, a lot of jobs require this particular skill set. At interviews, they pick you, how good you are at qualitative and quantitative research, check what you know about it at all. And then, as a matter of fact, six months pass and you are not involved in research once, but there may be many reasons for this, let's leave it out, but the fact remains that you need to know how to research. skill of research So the first thing is the You need to know the base and have some experience in this. If we are talking about the base, you should definitely read about types of research – what types of research are exists, how it may be implemented, how it is prepared, how you should gather information, what you should do with it afterwards. It's likely that everything you'll find on the internets is the ideal research process and how a researcher should be. But that's not a bad thing. You know the base and this will help you further, try to do the research yourself if you don't have that experience: just take any product and start looking for bugs and problems in it, read reviews. Do this research work algorithm to understand it better. skill of the researcher. An unobvious skill, which for some reason is overlooked or missed by many people, is . The way you speak, how you present your work, tell about yourself, will decide whether you will be hired or not. In the work of a modern UX/UI designer you have to talk and negotiate a lot, in an accessible and understandable way. You will communicate not only with your team of designers and developers, but also participate in all processes, including communication with the business (because it is important to adapt the design to business needs and goals that both benefit the company and satisfy the user).The ability to ask the right questions and the ability to talk about solutions, to explain the value and effectiveness of their solutions is the most important quality, which converts not only into a monetary equivalent, but also into a credit of trust on the part of customers. communication is just as important. You should care more than anyone else. You should be directly captured by the flow of any product, you should be curious to understand how the registration form works, or how this TabBar appears, what kind of nesting it has, where the application goes after the user clicked "send". And also being intensely curious about at what point the user will interact with the product. You'll find this skill very much helps you find creative solutions to design or improve some feature or product. Curiosity is parallel to the desire for self-development: it is a skill of constant learning, learning new techniques, trends and technologies. Curiosity . Not obvious, but super important, this is about accessibility and inclusiveness. You need to understand, for example, how interfaces are designed for users with disabilities, what tools are used to test such products. Empathy skill Above was everything that concerns soft-skills. And, of course, I'll mention hard skills, without which there is nothing nowadays. Knowing how to work with As strange as it may sound, it really helps in work. Neural network can write a good UX-text, write a flow for you, gather a competitors' base, write a script for testing, etc. Here you need to know how to ask the right questions and formulate queries. . ChatGPT Skill in working with different illustration generators or KV (key visual) ( ). Midjourney / Stable Diffusion You need to be able to master tools such as and . This is very important in day-to-day work and helps a lot with planning and teamwork. Jira Confluence Being proficient in animation and prototyping tools will also help you have an edge over other candidates. There are some cool and handy tools out there right now, is a prototyping app, is a cool tool for 3D animations, and s for creating 2D animations. I recommend you to explore them as well, they can come in handy in your work: both in product presentation and for creating any interface animations. ProtoPie Spline i Lottie Animation Know, understand and love web builders , , . Webflow Tilda Wix You, as a designer, should understand the principles of working in different frameworks. Such as , and others. Not to forget the – it's important for interface design.
Perhaps that's all I'd like to highlight and recommend to learn. Design thinking , Jobs To Be Done Lean UX laws of UX Your portfolio: tips and platforms The question about platforms for posting your portfolio is an important one, but honestly, I don't follow it myself as much as I probably should. Because I just can't find the time to do it, or I think - "nothing, I'll put it off for a better time". However, getting back to the question - it's ideal if you keep a diary, write a note - anything - every time you are faced with any task at work! This will help you then, in the future, to tell and describe the process of work and to identify from this task the positives and what you learned. But it's not only good for portfolios, it's also good for behavioral interviews. Because if you break down each of your work tasks, you can answer any behavioral question. Try to keep a diary or notes with detailed descriptions. Make wireframes of your awesome interesting cases every six months. And every year, try to pick and choose a new case study from your notes and wireframes.
Your portfolio should not contain 2 million works: here I worked in a printing house, and here I drew a banner, No, we are UX/UI designers, which means, well, maximum 5 cases you need to keep in your portfolio. And, of course, pay attention to the fact that we have to tell about the case in detail, namely: tell what you did, not the team; what the problem was; what framework was used or how you did your research (competitor analysis, survey, etc.) and demonstrate it; show low-frequency wireframes, diagrams, flowcharts, and the rest of the artifacts; talk about the results and figures. The best thing is to keep your portfolio on your own website. This can easily be done on Tilda or on Webflow - also a good tool. It's also very common nowadays for Senior level designers to use . Notion I don't recommend storing in , in . and especially not on Recruiters and the hiring team leader don't have time to go through long uploaded documents and large portfolios with more text. They only have an hour to review 50 portfolios. The rest of the time this team leader spends in calls. So make sure that your portfolio is as readable as possible, so that a quick glance will help recruitment understand everything. Figma pdf google disk. Business needs for good UX/UI designers and secrets of job search Answering the question about which businesses from which areas are now more likely to face a shortage of good UX/UI designers, I would say it's the segments of government organizations and industry. More often than not, they are always bad at UX/UI. But! I wouldn't advise you to look for a position there, because there are too complex and entrenched processes that will have to be shifted before something new is introduced. Let's imagine you're looking for a job in Poland, try putting that region on LinkedIn, see what companies are hiring designers, or what companies even exist/base themselves in the region you're looking for a job in. Try (remember your letter should be concise and simple so the recruiter has time to read it), look for internships. writing directly to the team or recruiter I also recommend paying attention to resources such as – I like it a lot. Also, of course, and, of course, there are various Telegram channels, where they also publish interesting vacancies, you should keep an eye on them. getmatch Otta I also recommend you to pay attention to these resources wellfound mind the product we work remotely Interviews: preparing I've had 40 interviews in my career, or even more. And that's because either the company didn't suit me, or I wasn't professionally prepared for such work. The most memorable was the first one. I was applying for a job with the guys who design road signs, and I really wanted to start somewhere, somewhere to work. I knew Photoshop and Illustrator by then. Anyway, they were asking me questions about my experience, what I was doing. And I was just showing my sister's work and some of my own to make me look more confident and professional. In general, I showed my sister's work - websites (I had no idea then how they were made), and my graphics. And when they started asking me very deeply about the website, I was confused. This is the most memorable, because you should not lie, do not attribute someone else's work to yourself. If you have no experience in something, try to do a project on your own, do some research, find some nuances in the product, propose a better solution. Test it. That way you will understand better what the job is all about, and you won't have to lie to your employer. As soon as I entered the design market, I had no idea that you should and can prepare for interviews. And there is so much information out there to help you interview well and get the offer you want. So at first I was very afraid of interviews, almost to the point of panic attacks. But then I started to study my mistakes, read articles, collect feedback from recruiters, write myself down. And everything got better, and now I am more confident in such situations. What is necessary and important: You've probably heard about it a hundred times. Check out the company blog, read articles, look for company representatives speaking at conferences, meetups, maybe they run some kind of their own Telegram channel. Read SEO interviews, look into the company's values and culture. You might even be able to find your teamleader and study their profile as well. Try to find reviews about the company, talk to someone who is already working. This is a stage, just like in our profession - a stage of analyzing and searching. Research a company. First, practice a short self-presentation: you don't have to answer the question "tell us a little about yourself" with a 40-minute presentation! Try to keep it to 3 minutes. Here you should tell about your recent and previous experience, and highlight important facts that just meshes with the company's wishes. If the company is looking for a designer with research skills and animation skills, try to mention that, tell them that you've been able to get in touch with that. I would also emphasize three points: a) talk briefly about, for example, the last 3-5 years of work (depends on experience) + accomplishments there; b) update your current experience + achievements there as well; c) describe your career goals, and why you are in search. Prepare a presentation about yourself. about each case study. Tip: Try to write down questions that come up in the interview about your cases so that you can cover them immediately at other interviews in the future. Prepare a portfolio and practice talking , they come in many forms. There are platforms with coaching for such questions. Practice behavioral questions you'd like to ask the company, the team, and maybe even the SEO. Think about what questions Helpful resources for coaching behavioral questions: biginterview pramp interview-warmup questions-to-ask article Interviews: how it goes First there is the You talk to the recruiter, he asks you simple questions: who you are, why you are looking for a job, your experience. The recruiter's task at this point is to find out how adequate you are, how you conduct the dialog, whether the company's wishes coincide with your skills. Usually the duration is no more than 30 minutes. screening process. Further, if everything is good and you fit all the parameters, the recruiter already passes the information about you to the team leader, and you are assigned a meeting with the team. can take up to a week. The waiting period The next stage is with the team. Here they will ask about your experience: on specific cases you will need to tell what you did, perhaps they will ask you to show a figma to understand how you maintain your workplace. Also at this stage they may ask you to solve some task. For example, they will ask you to show the registration process, this is where your approach to work is assessed. may also be asked: such as, tell us about a time when you had a very tight deadline / tell us about a colleague with whom you couldn't agree / tell us about a project where you made a mistake and it was critical. You need to answer honestly - this question is necessary to understand how you behave in stressful situations, how you cope with difficulties, how you organize your working time, whether you can prioritize tasks and whether you are an effective time manager. This is where it's time to get your notes sorted out. At the end of the interview, you may be asked to complete a test task. This stage can take from one to one and a half hours. a technical interview Behavioral questions The last stage could be or a meeting with the SEO. To summarize, there can be three or four stages, it all depends on the processes in the company. a defense of your test case solution Another common question is "why chose us" and "why are you looking for a job". Answer these two questions honestly. To answer the first one, a recertification will help you, highlight something important to you - the company culture or work processes - anything that interests you! Don't, of course, say you're only here for the money. Tell them why you decided to change jobs. The most common answer is that it is a need for professional growth, for example, you can answer like this: I am very grateful to company X, I have learned a lot, but I feel that I need growth, the tasks have become routine and simple for me, so I decided to go on a search. I would also like to add that there are several techniques for answering behavioral questions. For example one of the famous techniques is STAR: - (challange) a company wanted to increase the number of subscriptions with /through our service /situation - I needed to create a marketing plan that would help me achieve the goal. /task - action, I decided to use 3 different ones at the same time, we planned a few different family events and ran them /action - not only did we reach our goal, but we still made a 60% revenue. /result Read more about STAR here By the way, I've never been asked about "what do you see yourself as in the next 5 years." That's because it's really quite a complicated question, we live in such an unusually complicated time, I never thought I would be in emigration for two years, for example, so if you do get asked that question, try to think about your growth beforehand – how you see it: linear or vertical. Test tasks How to treat it and whether it are worth doing? No matter how many different managers I listen to, and no matter how many interviews I go on, no one has one, unified opinion. For some, it's enough to look at your work and talk about case studies. And someone needs to see how a candidate handles a test assignment. Therefore, if you are asked to do a test - agree if you are interested in the company and would really like to get there. On the test they look at your work process, your layout design, mastery of components, mastery of research skills and presentation skills. The better you do on the test, the better chance you have of grabbing that coveted spot, so be sure to reserch, show your workflow, surveys, artifacts. Also pay attention to your text! Don't make mistakes and typos in test jobs, ask questions if something is not clear. Read a helpful article about test-taking assignments What questions should I ask my employer? It is very important to think in advance about what you would like to learn about the company or the work process and tasks. In its turn, the company records how interested you are, and it's strange that you can't care about anything at all, try to compare it with your previous experience - what you cared about there, try to ask the recruiter this question somehow correctly. What are the company's/team's objectives for the next six months? What is the approval process for the new feature / workflow? What platforms will I have to work with? And what is the number of users? How is the research / do you have your own research center? What are your goals for the new candidate. What does he/she have to do to pass the probationary period? What skills are important to you in a candidate? And why exactly did you choose this company, why do you like it, and what, perhaps, are the disadvantages? I've also put together some helpful articles for you that will help you not to think about what questions you would ask your employer: unique-questions-to-ask-employers questions-you-should-be-asking Thank you for reading this article, use my advice, put it into practice and share your experience! I hope it was useful  💛🩷🩵

Coveted Careers: Mastering the Art of Securing Top UI/UX Design Roles in 2024

লোভনীয় ক্যারিয়ার: 2024 সালে শীর্ষ UI/UX ডিজাইনের ভূমিকা সুরক্ষিত করার শিল্পে দক্ষতা অর্জন

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प्रतिष्ठित करियर: 2024 में शीर्ष यूआई/यूएक्स डिज़ाइन भूमिकाएँ सुरक्षित करने की कला में महारत हासिल करना

切望されるキャリア: 2024 年にトップの UI/UX デザイン職を獲得するための技術を習得する

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Желанная карьера: овладение искусством поиска лучших должностей в сфере UI/UX-дизайнеров в 2024 году

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Những nghề nghiệp đáng mơ ước: Nắm vững nghệ thuật đảm bảo các vai trò thiết kế UI/UX hàng đầu vào năm 2024

令人垂涎的职业：掌握 2024 年获得顶级 UI/UX 设计职位的艺术

How to analyze comment sentiment and react automatically using AI Today, we're digging into a crucial topic for anyone who’s creating content for YouTube: How to analyze and respond to video comments quickly, using the sentiment in those comments. This tutorial is also handy for anyone who's running a YouTube channel and wants to grow engagement. Who cares about comments? We all know that the comments section on YouTube is where real magic happens. That’s where you have a chance to engage with your audience, hear their honest opinions, and build loyalty over time. Yes, nice comments are awesome. But the not-so-nice comments are important, too. they’re the ones you need to respond to the fastest. And An ideal system would work something like the one below. If you’re serious about growing your channel, you’ll want a deeper understanding of your audience. Analyzing comment sentiment gives a good gauge of the overall mood of your viewers—which helps you tailor your content. Truly, this could be a game-changer. Let's jump right in. Part 1: The tools for the job For this project, we’re using a platform called MindsDB—the platform for building custom AI. It basically connects real-time data—like tons of YouTube comments— to . It lets companies prototype and deploy AI-powered enterprise solutions quickly and at scale. AI models In this case, it acts as an orchestration layer where we bring everything together, using AI to analyze the sentiment in the comments. Today, we’ll be using models from OpenAI, which makes ChatGPT. Then we’ll set up some MindsDB automation and alerts—those will come from Slack—to help with instant responses. Here's what the workflow will look like in the end. Part 2: How to get everything set up Step 1. Connect YouTube to MindsDB To connect your YouTube account to MindsDB and be able to set up a chatbot, you need to first generate OAuth2 credentials in the Google Cloud Console and use it to connect YouTube to MindsDB. Find detailed instructions in our documentation . here Let’s name the connection mindsdb_youtube_oauth, which is referred to in the following tutorial. CREATE DATABASE mindsdb_youtube_oauth
WITH ENGINE = 'youtube',
PARAMETERS = {
    "credentials_file": "/path-to-creds-file/credentials.json"
    -- alternatively, use the credentials_url parameter
}; Once you connect YouTube to MindsDB successfully using the above statement, the mindsdb_youtube_oauth connection comes with the following tables: The comments table stores all data related to the comments left by the viewers, including when the comment was added, who added the comment, and the comment’s content. The videos table stores all data related to the videos, including title, description, and transcript. Next, we'll use OpenAI models to analyze the sentiment of the comments and generate replies. Step 2. Use an OpenAI model to analyze the sentiment of YouTube comments Before you can deploy OpenAI models in MindsDB, you should create an engine, providing an OpenAI API key as below. CREATE ML_ENGINE openai_engine
FROM openai
USING
    api_key = 'sk-xxx'; Now you can plug in any of OpenAI’s models into MindsDB using the CREATE MODEL statement and this engine. Let’s create a model that analyzes the sentiment of the comments. CREATE MODEL yt_sentiment_classifier
PREDICT sentiment
USING
    engine = 'openai_engine',
    model_name = 'gpt-4',
    prompt_template = 'describe the sentiment of the comments
                        strictly as "positive", "spam", or "negative".
                        "I love this video":positive
                        "It is not a helpful content":negative
                        "{{comment}}.":'; This model takes the {{comment}} value (from the comments table provided by the mindsdb_youtube_oauth connection created in Step 1) as input and gives the sentiment value as output. Join the comments table (from mindsdb_youtube_oauth) with the model to analyze the sentiment of the comments. Provide the channel_id value in the WHERE clause. SELECT c.comment, m.sentiment
FROM mindsdb_youtube_oauth.comments AS c
JOIN yt_sentiment_classifier AS m
WHERE c.channel_id="UC5_wBOLCWath6q1iTgPPD5A"; Here is sample output: comment sentiment This video explains the subject so well. positive Subscribe to this channel asap. spam It didn’t help me understand the subject. negative Step 3. Use an OpenAI model to generate replies to YouTube comments Create a model to generate replies to comments. Here the model will utilize the comment content (from the comments table) and transcript of the video (from the videos table) to come up with a reply. CREATE MODEL yt_reply_model
PREDICT reply
USING
    engine = 'openai_engine',
    model_name = 'gpt-4',
    prompt_template = 'briefly respond to the youtube comment "{{comment}}";
                       as a context, use the video transcript "{{transcript}}"'; This model takes the {{comment}} value (from the comments table) and the {{transcript}} value (from the videos table) as input and gives the reply value as output. Join the comments and videos tables on their common column being the video_id column. Then, join it with the sentiment classifier model and the reply generator model. This is how you can accomplish the chaining of models in MindsDB. (Before executing the below command, add at least one new comment to the channel, so that it can fulfill the LAST keyword condition.) SELECT c.comment AS comment,
       m1.sentiment AS sentiment,
       m2.reply AS reply
FROM mindsdb_youtube_oauth.comments c
LEFT JOIN mindsdb_youtube_oauth.videos v
ON c.video_id = v.video_id
JOIN yt_sentiment_classifier AS m1
JOIN yt_reply_model AS m2
WHERE c.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
AND v.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
AND c.published_at > LAST; Please note that for long videos the transcript will be long and that may result in the OpenAI token limit being exceeded. Alternatively, to pass long transcript values in the prompt to the model, you can use the feature of MindsDB. RAG Here is a sample output: comment sentiment reply This video explains the subject so well. positive Thank you for your comment. We’re glad you enjoyed the video. It didn’t help me understand the subject. negative Thank you for your comment. Please let us know your feedback on what could be improved. The above query joins the comments and videos tables on their common column, which is the video_id column. The reason for joining these tables is to provide input to both the models—the sentiment classifier model requires the comment column from the comments table, and the reply generator model requires the transcript column from the videos table. Next, the two models are joined using the custom JOIN statement that does not require any ON clause condition because each model is provided with the required input from the data tables. You can select the predictions made by the models as shown in the SELECT clause. Finally, we define the channel_id value in the WHERE clause. The condition that uses the LAST keyword on the published_at column enables you to fetch only the recently added comments. Now that the sentiment of comments is analyzed and replies are generated, let’s add some automation. Step 4. Post replies to positive comments This is the first component of the job that we’ll create in Step 7. Here is how you can insert replies to recent comments whose sentiment has been classified as positive: (Before executing the below command, add at least one new (positive) comment to the channel, so that it can fulfill the LAST keyword condition.) INSERT INTO mindsdb_youtube_oauth.comments (comment_id, reply)
  SELECT c.comment_id AS comment_id,
         m2.reply AS reply
  FROM mindsdb_youtube_oauth.comments c
  LEFT JOIN mindsdb_youtube_oauth.videos v
  ON c.video_id = v.video_id
  JOIN yt_sentiment_classifier AS m1
  JOIN yt_reply_model AS m2
  WHERE c.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
  AND v.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
  AND c.published_at > LAST
  AND m1.sentiment = 'positive'; The LAST keyword ensures that only the newly added comments are returned by the query. Step 5. Notify about spam comments This is the second component of the job that we’ll create in Step 7. Let’s automate notifications to Slack about spam comments. A notification will include all details about the comment, its sentiment (predicted by the model in Step 2), and a sample reply (generated by the model in Step 3). Set up your Slack channel and connect it to MindsDB following . this instruction CREATE DATABASE yt_slack
WITH
  ENGINE = 'slack',
  PARAMETERS = {
      "token": "xoxb-xxx"
    }; Test the connection by inserting a message into the Slack channel. INSERT INTO yt_slack.channels (channel, text)
VALUES("channel-name", "Test message."); Here is how you can send notifications to Slack about recent comments whose sentiment has been classified as spam: (Before executing the below command, add at least one new (spam) comment to the channel, so that it can fulfill the LAST keyword condition.) INSERT INTO yt_slack.channels (channel, text)
    SELECT "channel-name" AS channel,
           concat('Video: https://www.youtube.com/watch?v=', c.video_id, chr(10),
                  'Spam Comment: https://www.youtube.com/watch?v=', c.video_id, 
                        '&lc=', c.comment_id, chr(10),
                  'Author: ', c.display_name, chr(10),
                  'Comment: ', c.comment) AS text
    FROM mindsdb_youtube_oauth.comments c
    LEFT JOIN mindsdb_youtube_oauth.videos v
    ON c.video_id = v.video_id
    JOIN yt_sentiment_classifier AS m
    WHERE c.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
    AND v.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
    AND c.published_at > LAST
    AND m.sentiment = 'spam'; The LAST keyword ensures that only the newly added comments are returned by the query. Step 6. Notify about negative comments This is the third component of the job that we’ll create in Step 7. Now, what about comments with negative sentiment? As these require analysis and thoughtful answers, let’s automate notifications to Slack about negative comments. A notification will include all details about the comment, its sentiment (predicted by the model in Step 2), and a sample reply (generated by the model in Step 3). Set up your Slack channel and connect it to MindsDB following . this instruction CREATE DATABASE yt_slack
WITH
  ENGINE = 'slack',
  PARAMETERS = {
      "token": "xoxb-xxx"
    }; Test the connection by inserting a message into the Slack channel. INSERT INTO yt_slack.channels (channel, text)

VALUES("channel-name", "Test message."); Here is how you can send notifications to Slack about recent comments whose sentiment has been classified as negative: (Before executing the below command, add at least one new (negative) comment to the channel, so that it can fulfill the LAST keyword condition.) INSERT INTO yt_slack.channels (channel, text)
    SELECT "channel-name" AS channel,
           concat('Video: https://www.youtube.com/watch?v=', c.video_id, chr(10),
                  'Negative Comment: https://www.youtube.com/watch?v=', c.video_id, 
                        '&lc=', c.comment_id, chr(10),
                  'Author: ', c.display_name, chr(10),
                  'Comment: ', c.comment, chr(10),
                  'Sample reply: ', m2.reply) AS text
    FROM mindsdb_youtube_oauth.comments c
    LEFT JOIN mindsdb_youtube_oauth.videos v
    ON c.video_id = v.video_id
    JOIN yt_sentiment_classifier AS m
    JOIN yt_reply_model AS m2
    WHERE c.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
    AND v.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
    AND c.published_at > LAST
    AND m.sentiment = 'negative'; The LAST keyword ensures that only the newly added comments are returned by the query. Step 7. Automate replies to positive comments and notifications about negative and spam comments Let’s create a job that will reply to recent positive comments, send notifications about recent negative comments with draft responses, and send notifications about recent spam comments. To do that, we need to connect a database to MindsDB in order to save the recent comments into a table. (The reason for doing so is that every run of a query that includes the condition with the LAST keyword returns only the newly added comments, which haven’t been returned in the previous run of such a query. To be able to do different actions for positive and negative comments, we need to save the output of the query with LAST. To save a batch of recently added comments returned by the query with LAST, we need a database table. Learn more about the .) LAST keyword here You can connect a database to MindsDB using the CREATE DATABASE statement and providing specific parameters. Choose one of the on how to connect it to MindsDB. supported databases and follow the instructions Here, we connect a PostgreSQL database as below: CREATE DATABASE psql_datasource
WITH ENGINE = 'postgres',
PARAMETERS = {
    "host": "host-name-or-ip-address",
    "port": 5432,
    "database": "database_name",
    "schema": "schema_name",
    "user": "postgres",
    "password": "password"
}; To create a table and insert into it the output of the query with LAST, use this command: CREATE OR REPLACE TABLE psql_datasource.recent_comments (
      SELECT *
      FROM mindsdb_youtube_oauth.comments c
      LEFT JOIN mindsdb_youtube_oauth.videos v
      ON c.video_id = v.video_id
      WHERE c.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
      AND v.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
      AND c.published_at > LAST
); Now, it’s time to create a job that automates steps 4, 5, and 6. CREATE JOB youtube_chatbot (

  -- save the recently added comments into a table

  CREATE OR REPLACE TABLE psql_datasource.recent_comments (
    SELECT *
    FROM mindsdb_youtube_oauth.comments c
    LEFT JOIN mindsdb_youtube_oauth.videos v
    ON c.video_id = v.video_id
    WHERE c.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
    AND v.channel_id="UC5_wBOLCWath6q1iTgPPD5A"
    AND c.published_at > LAST
  );

  -- automate replies for positive comments (from Step 4)

  INSERT INTO mindsdb_youtube_oauth.comments (comment_id, reply)
    SELECT c.comment_id AS comment_id,
           m2.reply AS reply
    FROM psql_datasource.recent_comments AS c
    JOIN yt_sentiment_classifier AS m
    JOIN yt_reply_model AS m2
    WHERE m.sentiment = 'positive';

   -- automate notifications about spam comments (from Step 5)

   INSERT INTO yt_slack.channels (channel, text)
     SELECT "channel-name" AS channel,
            concat('Video: https://www.youtube.com/watch?v=', c.video_id, chr(10),
                   'Spam Comment: https://www.youtube.com/watch?v=', c.video_id, 
                         '&lc=', c.comment_id, chr(10),
                   'Author: ', c.display_name, chr(10),
                   'Comment: ', c.comment) AS text
     FROM psql_datasource.recent_comments AS c
     JOIN yt_sentiment_classifier AS m
     WHERE m.sentiment = 'spam';

  -- automate notifications about negative comments (from Step 6)

  INSERT INTO yt_slack.channels (channel, text)
    SELECT "channel-name" AS channel,
           concat('Video: https://www.youtube.com/watch?v=', c.video_id, chr(10),
                  'Negative Comment: https://www.youtube.com/watch?v=', c.video_id, 
                        '&lc=', c.comment_id, chr(10),
                  'Author: ', c.display_name, chr(10),
                  'Comment: ', c.comment, chr(10),
                  'Sample reply: ', m2.reply) AS text
    FROM psql_datasource.recent_comments AS c
    JOIN yt_sentiment_classifier AS m
    JOIN yt_reply_model AS m2
    WHERE m.sentiment = 'negative';
)
EVERY 10 minutes; This job (re)creates the recent_comments table and stores only the recently added comments in it. This table is joined with the models to reply to only positive comments. Next, this table is joined with the sentiment classifier model to send notifications about spam comments. And finally, this table is again joined with both models to send notifications about negative comments with draft responses. Please note that for large workloads of comments data, it may be required to increase the . YouTube quota What a custom YouTube chatbot means With the above steps, you can connect YouTube to MindsDB to access your channel’s comments, analyze them with the help of AI, and automate replies to the recently added comments (or send notifications about the recently added comments). In this tutorial, we've shown how to set up a chatbot for a YouTube channel defined in the WHERE clause while querying the comments and videos table. You can customize this chatbot to your use case, utilizing other integrations and features provided by MindsDB. Why analyzing sentiment is so important Analyzing to determine whether it’s positive or negative is gold when it comes to understanding your audience's emotions. language in comments Believe it or not—negative comments, while not fun, are not the enemy. They're an opportunity. They give you valuable feedback that helps you grow as a creator or as a brand. Some of the most dedicated viewers start as critics. When you respond quickly and gracefully to their nastiest comments (which shows that you value their feedback), you really can turn critics into loyal fans. Remember, it's not about proving anyone wrong; it's about responding fast (in real-time, which is possible with MindsDB) and building a connection. Also published . here

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Since 2016

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