In 1950, computer scientist and philosopher Alan Turing published a paper on ‘Computing machinery and intelligence’ that is often referred to as the origin of modern artificial intelligence. In it, he described the capacity for computers of the future to to display human-like capacities such as reasoning, learning, planning and creativity.
Artificial intelligence as a field began developing in the 1960s around the idea that it should be possible to deconstruct intelligent human behaviors as a succession of logical rules, transcribed in algorithms, which machines could follow to display intelligent behavior. As learning is one of the key features of human intelligence, scientists derived ways to train the computers to become so familiar with certain topics that they could identify the key components of those topics automatically. For example, if the objective is to teach a machine to recognize pictures with cats, the computer is fed with thousands of pictures, including pictures with cats. The learning capacity of these machines is based on the ability of the algorithm to find statistical correlations in the data it analyses, that is to say, interdependence of variables in the data – or in layman’s terms, finding the cat in the haystack.
By applying the methodologies of how humans learn to identify object patterns, artificial intelligence leverages a computer’s ability to analyze huge quantities of data to find statistical correlations, in essence to deploy human learning methods at scale. Machine logic does differ from human thought pattern, and a fundamental aspect of machine learning techniques is that there is no way to know how it makes its decision on a given task. In computer logic, the associations necessary to fulfill the given task are left to the computer itself to define. Recently, when Facebook AI researchers enabled bot to bot discussion, they had to shut down the experiment as the bots had developed their own “shorthand” in communication, attributable to the computer’s desire to make communication more efficient.
Today, artificial Intelligence can be used to write stories or create artworks such as paintings or musical compositions, as well as analyze large sets of data. Advances in AI have established two distinct types of machine learning, called “Narrow” and “Strong”. Data-driven AI is referred to as ‘narrow AI’ or ‘ weak AI’ because it creates machines that are only able to do one task very well: recognize cats; go play; invent a recipe. Narrow artificial intelligence systems lack common sense and intentionality, and it is still not possible for machines to understand what would come next in a series of images or to understand the broader context of a scene in a given image.
Strong artificial intelligence, on the other hand, harks back to the original AI quest to create machines that are able to display the same level of intelligence as humans. Often referred to as artificial general intelligence or ‘strong AI’, this type of machine learning would perform different tasks, show common sense and share intentionality. Outstripping human intelligence, Strong AI would lead to a technological singularity’, leaving humans in the hands of machines. And that is where artificial intelligence gets a lot more real.
Watching the recent Supreme Court television coverage and the wide range of emotions shown by all parties involved gave me pause to wonder whether artificial intelligence could be effectively deployed to analyze emotional response in humans.
While studying emotions is important for a number of reasons, artificial intelligence may not be able to cope:
Emotions are the most unpredictable aspect of a person, but also a common aspect of the human condition;
An emotion shows the way that a person perceives the world, and an accurate categorization of emotion could be a better indicator of truthfulness or deception;
Emotions are an important aspect of human intelligence and play a significant role in human decision-making processes.
However, there is little information about what emotions really are, and the boundaries to the domain of what experts have called emotion are so blurry that it sometimes appears that everything is an emotion.
While emotions are a common aspect of the human condition, it should be evident that waiting for a consensus on how experts actually categorize emotions is unrealistic because the study of emotions is still incomplete. There is some acceptance of classifying emotions according to their physical manifestation, i.e. humans show emotion on their faces and in their body movement, and those cues could help classify and categorize emotional response. But each of us is different, and it is perhaps our pre-conditioning that dictates not only the emotional response but also the level of that response. Someone who was taught to foster joy may react differently than someone who is serially depressed when exposed to the same stimulus – hence the notion that emotions are unpredictable.
A main problem for categorizing emotions stems from language, because there are some emotion words that have different meanings in different countries, kind of like how Eskimos have hundreds of words for the condition of snow, but most folks just call it “snow”. Nevertheless, structuring emotions to be interpreted by AI means finding a common ground for the emotion words, even if the categories and classifications are different in different cultures. This may be impossible to codify, and certainly would be reductive as emotional responses and triggers evolve over time and with human experience. At one time, cars frightened people, and while today some people’s ability to not use a turn signal may be frightening, the aspect of driving a car or seeing a car does not strike the kind of fear in humans it once did.
Motoring is one of the most contemptible soul-destroying and devitalizing pursuits that the ill-fortune of misguided humanity has ever imposed upon its credulity…[they are] a pack of fiends released from the nethermost pit. – C. E. M. Joad, circa 1900
In addition, the notion of “mixed emotions” about a topic are inherent in humans as well, which may defy categorization – like the old joke about someone seeing their Mother In Law drive off a cliff in their new sport scar. One of the theories put forth is commonly known as the Strongest Emotion Model, which seeks to address this mixed emotions dilemma by assigning values for each emotion felt, and tagging the one that has the highest value as the predominant, and ultimately motivating emotional response.
While facial expressions can also be tied into mixed emotional response, they may not agree with the verbal cues offered as support of underlying emotion. If you watch the SCOTUS court proceedings, there are often facial expressions that seem to run counter to what is being said, and those facial expressions can be viewed as a more accurate representation of underlying emotion – like telling someone their disgusting dinner dish is tasty while wrinkling the nose, or when during a poker game a great hand and the exhilaration of the win is masked by a poker face. It gets deeper, as some emotions have no expression whatsoever, and that there are some others that have the same nuances across emotion, and thus, it is impossible to differentiate between them.
The goal of using artificial intelligence to analyze emotions is a noble direction in which to take machine learning. However, as humans offer such a wide variable to study, I would argue that a concrete basis on which to formulate artificial intelligence for the accurate assessment of the dynamics of human emotion is too lofty a goal for current technology.
This article was composed using the Zaphne content inspiration tool for original research. Sign up for a free demo of the Zaphne Fire platform at https://calendly.com/zaphne
The process of qualifying a lead. is critical because we want to make sure we are using our sales resources to talk to people who can actually become customers. Often, startups will use a mix of inside and outside sales strategies. Because so many startups use an inside sales model primarily, let’s dig into how it works. Involves speaking to people at the lead stage, determining if they meet our criteria to become opportunities, and if so, scheduling time for them to learn about our product in a sales meeting.
The person who makes this happen is a:. Sales Development Rep. The SDR is an entry-level sales person. The Sales Manager might initially be the founder, then a Senior Account Executive and then perhaps a VP of Sales. This metric helps us predict growth and can guide us on how many new sales reps to hire.
We need to make sure that the tactics that marketing uses are tightly aligned with the tactics that sales uses. Our sales and marketing goals should be planned together. The sales team relies on marketing to bring in qualified leads and the marketing team relies on sales to engage and close. The leaders of sales and marketing on our team should be meeting regularly, reviewing progress and discussing any challenges. The agreement might dictate that each month, marketing will generate 100 leads, and sales will reach out to them within 24 hours.
Digital payments major Paytm said it has acquired Bengaluru-based savings management startup, Balance Technology for an undisclosed amount. The acquisition will help One97 Communications, which operates the Paytm brand, in further enhancing its user and merchant interfaces, Paytm said in a statement. While Paytm declined to comment on the deal size, the transaction is expected to be about USD 2 million as per industry sources. We are excited to welcome the Balance Technology team to Paytm. They have created a fantastic product with real user engagement.
As we constantly look to create customised and intuitive user experiences, the Balance Technology team will be an invaluable part of this journey, Paytm Chief Financial Officer and SVP Madhur Deora said. The six-member team of Balance Technology has joined the SoftBank and Alibaba-backed company’s product and design team. He added that the company will use its capabilities in computational intelligence, design and proprietary algorithms to help Paytm users. According to Balance Technology’s website, the company helps users invest as per goals that they have set, allowing them to earn up to 8.7 per cent in returns without lock-in periods.
Number of African tech startups funded rises 17% in 2016
African tech startups raised funding in excess of US$129 million in 2016, with the number of startups securing funding up by 16.8 per cent compared to the previous year. According to the DISRUPT AFRICA TECH STARTUPS FUNDING REPORT released today, 146 startups from across Africa raised US$129,113,200 in funding over the course of 2016. This displays substantial growth in the number of startups to raise funding as compared to the previous year. Although the overall total amount of funding recorded declined. Nigeria and Kenya remained the three most popular investment destinations on the continent, accounting for 80.3 per cent of funds secured.
Egypt experienced over 100 per cent growth in fundraising, making it the fourth ranked destination. Of the nine sectors analysed in the report, the fintech sector received the most backing in 2016, with startups in this space raising a combined US$31. New to this edition, the report also makes available data on the startup acquisitions which took place in 2016; as well as the results of surveys relating to preferences and trends within the entrepreneur and investor communities on the continent.
Citi invests in fixed income e-trading technology startup
Citi has made a strategic investment in an electronic trading technology startup for fixed income and derivatives markets, The TRADE can reveal. TransFICC, which specialises in low-latency connectivity, has secured funding from Citi and has become the first external company to join the investment bank’s Innovation Lab in London. Citi launched its London-based Innovation Lab in February, supporting the bank’s markets and securities services business globally with a focus on building out new technologies including data science, visualisation and high-performance computing. Focused on resolving issues of market fragmentation, TransFICC launched in 2016 with an application programming interface system for banks and asset managers, which provides financial institutions access to various e-trading venues, while reducing costs and streamlining technology. One of the major barriers to accessing new venues in fixed income, with currently more than 200 venue APIs in the market, is the time and costs of coding, according to TransFICC founder, Steve Toland.
During setup, the program creates a startup registration point in Windows in order to automatically start when any user boots the PC. A scheduled task is added to Windows Task Scheduler in order to launch the program at various scheduled times. The software is designed to connect to the Internet and adds a Windows Firewall exception in order to do so without being interfered with. The primary executable is named gpu-z.exe. The setup package generally installs about 25 files and is usually about 1.37 MB.
Program details. GPU-Z.exe is scheduled as a task named ‘TechPowerUp GPU-Z’. Scheduled Task. GPU-Z.exe is automatically launched at startup through a scheduled task named GPU-Z. Startup File.
GPU-Z.exe is added as a firewall exception for ‘C:Program FilesGPU-ZGPU-Z.exe’. Or, you can uninstall TechPowerUp GPU-Z from your computer by using the Add/Remove Program feature in the Window’s Control Panel. 32.05% of installs come from the United States.
In 2017, $69.51 billion was spent on pets in the U.S., according to the American Pet Products Association. As a whole, the global pet market is estimated at $109 billion. So it’s no surprise that the increased spend on pets is reflected in increased funding for pet-related startups. Funding in pet startups surged by 334 percent to $291.8 million compared to $67.2 million in 2012, according to Crunchbase research. Funding totals in pet-related startups have already reached $519.3 million in 2018-78 percent higher than all of last year.
Then in May, another dog-walking and pet sitting service, Rover, brought in $155 million in a tech growth round. Looking abroad, Rover also recently announced its expansion into Europe-starting with the United Kingdom this July-which represents 25 percent of the global pet care market. On the venture side, Mars Petcare and Digitalis Ventures launched the $100 million Companion Fund to focus exclusively on pet care innovation in areas such as health, diagnostics, nutrition, and services. It’s the first pet care venture capital vehicle, according to Mars’ head of ventures Ben Jacobs, who is also a founder of Whistle, which developed a device and mobile app to monitor a pet’s activity and health. The fund’s goal is to help finance and support pet care founders.
In addition to the Companion Fund, Mars launched the Leap Venture Studio-the first pet care focused accelerator which was formed in partnership with R/GA Ventures and Found Animals. As a former operations consultant, Renaldo saw firsthand the inferior ingredients and substandard cooking processes used to make kibble and other mass-market pet food.
University of Texas at Dallas Alum, Systems Analyst by profession who is inclined towards Business and Technology. After 16 years my family moved to Ujjain, India when I was in class 11th. This year was a provoking year as I cleared State Level Mathematics Olympiad and appeared in National Mathematics Olympiad, sponsored by Government of India. This interest provoked me to opt for an undergraduate degree in Computer Science and after my High School I went to Solapur, India for my under graduation. I opted for an undergraduate degree in Computer Science and Engineering from Walchand Institute of Technology, Solapur.
After my under graduation I moved to Pune, India to start my professional career at HSBC Global Technology. My real motivation behind pursuing a degree in management was my work experience as a Software Configuration Manager at HSBC Global Technology India. After 1.5 years I resigned HSBC and came to pursue my Masters in Information Technology & Management from The University of Texas at Dallas. Being a graduate student of Information Technology & Management seems to be an endless journey of discovery and knowledge, revealing the infinite possibilities that a business concept can give shape to. I ran a Micro-ISV focusing on web development and social media consulting for small business and startups.
My blogs talk about emerging social platforms, social media services, startup success and entrepreneurs. You can find me on almost all the social networking portals and can get in touch with me. Those who read 6 degrees of separation – and those who make you think about 1 degree of Social Network.
The 8 Hottest Tech Start-Up Perks You Wish You Had: Gothamist
Warbly Shark Fur, which sells face toboggans online, has a Bagel Gazebo stocked dangerously full for its employees. Client-conscious workers don’t have to worry about staining their teeth on that luscious, inky-black brew: there’s a teeth whitening bar next to the break room. Mangoes are freshly cut with machetes in SheeBloop’s lobby, but Donaldson encourages workers to use their feeding tubes. Joe Geaux helps their clients pretend to speak French, so it’s only natural that their employees enjoy Francophilic perks. Mandatory Monte Cristo Mondays, in which workers construct the sandwiches blindfolded in a windowless room full of birds, has been an institution since the firm’s inception.
At the Midtown flat of Hail Ceaser, a firm dedicated to designing emojis of caesar salads, workers stare at a giant whirring fan with fourteen foot blades until their hunger subsides. When the fan is broken, employees can use the company’s Seamless account. Ergonomic dining tables greet the staff at Betsy, an e-commerce site designed for people named Betsy. Rotating chefs in the company dining hall means that they’ll never eat the same meal twice in one month. It all builds up to Sushi Thursdays, the last Thursday of every month in which the freshest wares are flown in from Tokyo’s famed Tsukiji Fish Market.
All the employees working out of FundFund’s Battery Park City office are given free use of the company’s car service and Private Zip Line. While the company’s stated purpose is unknown, FundFund’s employees are treated to a money-burning in the atrium on the last work day of every month.
We Build CommunitiesIf you are a Tech startup entrepreneur who is just starting, or have been around for a while, You are invited to be part of the Community that exists in Chennai – Chennai Open Coffee Club. We Mentor Entrepreneurs 1:1We do professional consultations with entrepreneurs who are either looking for feedback on a Business Idea or are looking for inputs on a specific issue related to your startup enterprise. If you need inputs on topics as such Fundraising strategy, Board Formation, Corporate Structuring, Product Launches, Team Building, Idea Validation etc, You are in the right place. We Have WorkSpaceEarly stage entrepreneurs need a space to work when they start with their ventures. For teams of upto 4 members we offer space at nominal rates.
Everything you need to get started is made available, just bring your computers to get started. If you / your team would like to avail this, Get in touch. We organize EventsTime and time again there are specific topics that come up from entrepreneurs and as a way of effectively addressing them, We organize regular webinars and workshops. Once a year we organize Startup Walk where the startups in the city open their doors and participate in an open house to host people who are interested in seeing the Chennai Ecosystem upclose. Periodically we also organize Prototyping Events where teams come together and build prototype of solutions for real problems.
Mentors participate to help the teams through the process. At the end of it, they present to a jury of experts and get feedback and insights.
Regional Startup Ecosystems: The Next Tech Startup Hub Is Everywhere
Everyone wants to run a startup – even the big boys and girls. Given all of these converging strands, the experts at the Global Entrepreneurship Network and Bay Area consultancy Startup Genome are onto something. This spring they released their second annual Global Startup Ecosystem Report, ranking metro-area clusters or hubs within 12 sub-sectors with the help of data from Crunchbase, Tech Nation, Orb Intelligence and Dealroom. Here, with Startup Genome’s permission, we present an adapted section of the 252-pp. Global venture capital investments in startups hit a decade high in 2017, with over $140 billion invested.
Total value creation of the global startup economy from 2015 to 2017 reached $2.3 trillion – a 25.6-percent increase from the 2014 to 2016 period. The types of companies that fueled the first and second generation of global startup ecosystems – social media apps, digital media, and other pure internet companies – are declining. Top startup hubs like Silicon Valley, London, and New York continue to dominate top-level activity and maintain their status as the top performers for most sub-sectors. The shifts in the startup map, both geographic and economic, are signals that we are heading into a new era of tech. In this new era, successful startups will do one of two things: 1) Tackle specific Third Wave verticals – think Uber for mobility or Airbnb for hospitality – or 2) Rely on Deep Tech – i.e.
build businesses through technological breakthroughs, e.g. distributed ledgers, AI, or Life Sciences. In 2017, VC funding for startups in the United States and in the Asia-Pacific region was even, with each accounting for 42 percent of investment value. To build the entrepreneurship ecosystems of the future, the key takeaway in this new era of tech is that ecosystem builders need to not only look at tech as a whole, but pay attention to and invest in specific startup sub-sectors.
Established tech hubs continue to lead, but startup hubs are emerging in new, smaller places. The catch: Startup financing overall is on the wane. As Silicon Valley and the San Francisco Bay Area in general have become increasingly expensive for both companies and talented people, some commentators have argued that high-tech startups are spreading to smaller cities and metropolitan areas, many of which are in the industrial heartland. New research by my colleague and collaborator Ian Hathaway of the Center for American Entrepreneurship, a Washington think tank, takes a detailed look at whether the geography of tech startups and startup hubs in America is changing. America’s startups remain highly concentrated in a small number of hubs.
The concentration of first financings among these leading hubs has risen since 2009. A number of Rust Belt and older industrial cities-Detroit, Cleveland, Cincinnati, Milwaukee, Allentown, Albany, Grand Rapids, and Buffalo-have seen declines in first financings, as have more industrial and resource-dependent Sunbelt cities like Tulsa, Oklahoma City, and Memphis. Startup financing is still massively concentrated, but some smaller places, mainly college towns and cities like Pittsburgh, are seeing some growth. Pittsburgh appears to be the one older industrial center that is maybe growing into a startup hub, along with the post-industrial cities of Columbus and Indianapolis and, of course, college towns. Hathaway stresses that it takes a long time for new startup hubs to develop, and city leaders and policy-makers need to be realistic about the scope, pace, and inevitability of the rise of the rest.
The most the disturbing finding in the report is the substantial overall decline in startup financings in recent years. This is in line with a growing body of research, some of it by Hathaway, that points to a decline in startups and entrepreneurship in the United States.
Government overreach is killing this Mississippi tech startup
Mississippi should encourage innovative business ventures, not squash them because established industries don’t like new competition. Mississippi’s occupational licensing laws – especially in the hands of self-interested regulatory boards – threaten technological innovation and the rights to free speech and to earn an honest living. We are learning this firsthand because our innovative tech startup, called Vizaline, has been targeted for elimination by the Mississippi Board of Licensure for Professional Engineers and Surveyors. The more information banks have about their properties, the better. Less uncertainty means safer loans, safer banks and safer customers.
More: Madison tech-biz says rights are being violated by state board trying to shut him down. Vizaline uses publicly available data – legal descriptions written into deeds – to draw lines on satellite photos for banks. The board, which is made up of only licensed surveyors and engineers, is twisting Mississippi’s surveying laws. The board cannot stop our business from speaking just because it sees us as potential competition. If a Mississippi regulatory board can sue to shut down our speech and our business by twisting occupational licensing laws, no new business idea in Mississippi is safe.
We might not be the next Google, but we are a growing small business providing an in-demand service to banks across the South. What the board is trying to do is both short-sighted and unconstitutional.
Most startups request an exclusive license because they believe it is required to raise funding for the company. YALE STARTUP LICENSE. Yale strongly encourages innovators with non-therapeutic discoveries looking to start companies to take advantage of our pre-negotiated Startup License. The Startup License is based on transparency and fairness, offering the exact same, very favorable terms to all Yale startups. Further, by reducing all uncertainty as to the terms of the license, startups can comfortably take an option to license the technology, thus deferring the need to sign the license until such time that they feel ready to assume the responsibilities of a licensee.
While Yale’s primary mission in licensing technology to startups is to promote the development of products or services that benefit society based upon Yale research, Yale does seek a reasonable financial return from its licensees so that it can reinvest in its education and research missions. STARTUP LICENSE PROCESS. For Yale entrepreneurs demonstrating a diligent effort to start a company based on Yale technology that includes one or more Principal Investigators as founders of the company, the process of getting a Startup license is very simple. Entrepreneurs may then execute the Startup License immediately, or, if still in the formative stage, extend their option as they seek to raise financing or other sources of cash that will allow them to make the payments required once the license is executed. Benefits to Startups and to Yale Community: Reduces the time and legal expense to get a license done, freeing time and resources to focus on developing business.
Offers predictable, consistent, and fair license terms to all startups. YALE THERAPEUTICS LICENSES. Therapeutic startups are not eligible for the Yale Startup License. NIH-funded research in the biosciences represents the bulk of funded research at Yale, and as a consequence, almost all of the most significant startups with licenses from Yale are for drug discovery technologies and/or for therapeutic agents themselves. Rather than view large companies as lesser-preferred alternatives to a startup, many of our startups have been launched with the participation of pharmaceutical companies, either with license to a very limited field, research collaboration or sponsorship, and/or investment from their corporate venture group.
After the 2016 funding winter, the year 2017 witnessed a lot of course-correction in all sectors, thereby building the investor’s trust over the Indian startups again. As a result, over 34 new tech startup funds were launched in 2017, raking in over $2.3 Bn funds, reveals Inc42’s Annual Indian Tech Startup Funding Report 2017. The report also highlights the active contribution of the Indian corporate sector in setting up new startup funds. Of the 34 newly launched funds, 21 funds were launched by corporates while six funds were led by the Indian government or government bodies. Besides these new funds, over 14 existing startup funds raised a new fund for India investments or disclosed plans of raising a new fund with a combined corpus of $986 Mn.
Also, the report identifies 10 new startup funds which are yet to be launched to invest in the Indian tech startup ecosystem, including the likes of VC Fund Vedanta Group Founder, Sandeep Aggarwal Family Fund, The Fundamentum Partnership, HDFC Bank Startup Fund, Xiaomi Startup Fund and more. Interestingly, of the upcoming tech startup funds, five are corporate funds. Alteria Capital: The co-founders of Mumbai-based venture debt fund InnoVen Capital Ajay Hattangdi and Vinod Murali launched Alteria Capital, a debt fund with a corpus of about $157 Mn. The Category II investment fund, will have a tenure of seven, with a possible extension of two years. The fund is looking to make the first close of the fund by the first quarter of 2018.
Alteria Capital will have an average ticket size from $471K – $15.7 Mn. Unitary Helion: Rahul Chandra, MD, Helion Venture Partners announced to float $100 Mn worth Unitary Helion tech fund in May 2017 and raised the first corpus in October 2017. Epiq Capital India Fund: Mumbai-based PE firm Epiq Capital announced the first close of its $200 Mn-$250 Mn maiden tech startup fund in November 2017. Stellaris Venture Partners: An early-stage startup focussed fund, Stellaris Venture invests in global SaaS, applications for Indian small and mid-sized business and consumers in large verticals such as healthcare, education, financial services, and retail. Trend Micro Startup Fund: Trend Micro launched a $100 Mn corporate venture fund in June 2017 with an aim to nurture a portfolio of startups in emerging ecosystems such as the Internet of Things.
As one of the nation’s leading research institutions the University of Rochester has brought education, research, and commercialization together to become a major hub of innovation and economic growth. The University of Rochester STARTUP-NY Plan has designated 105,894 square feet of space at High Tech Rochester’s Lennox Tech Enterprise Center and at two buildings within Eastman Business Park. Governor Cuomo’s groundbreaking START-UP NY initiative will give approved companies tax exemptions for 10 years, when they locate on designated areas associated with colleges and universities and align with a school’s core academic mission. The University of Rochester’s START-UP NY plan is focused on attracting eligible companies in the broad fields of science, engineering, social science, health science, business, and music. Research: Companies commercializing University of Rochester research or with technology interests that align with University programs and can be further developed through collaborations.
Training, experiential learning or mentoring: Learning opportunities for students and trainees can be facilitated between companies and University of Rochester programs or centers. Access to facilities/research infrastructure: Companies may have use for some of the shared research facilities and centers at the University of Rochester. Applications will be evaluated for factors including: economic and community benefit, business model, technology cluster and alignment with specific University domains of excellence and mission. Businesses interested in partnering with the University of Rochester should initially contact Adam Tulgan at adam. Applications reaching the second stage of review will be evaluated more comprehensively for factors including: economic and community benefit, business model, technology cluster and alignment with specific University domains of excellence and mission.
The evaluations will be conducted by a Review Committee comprised of representatives the University of Rochester, High Tech Rochester, Excell Partners, Eastman Business Park, and the community leaders. The University of Rochester STARTUP-NY plan designates 105,894 sq.