Daily Archives: March 27, 2022

There was a lot to like about President Bidens first State of the Union address, but sadly, I disagree with his conclusion. The state of the union is not strong; in fact, the American people have rarely been less united. And the political rupture that threatens to tear our nation apart is largely occurring along the urban/rural divide.

The causes of this division are many and the solutions are often daunting or obscure, but it is impossible to deny that one of the largest contributing factors has been the extreme geographic inequality that has grown over the past four decades of bipartisan neoliberal rule. Throughout rural America, once-vibrant factory towns have been impoverished and dismantled through the offshoring of manufacturing jobs. Local businesses have been struggling to compete against the concentrated buying power of national chains, while local workers have been forced to struggle to make ends meet as monopsony employers have relentlessly pushed down wages. Small and midsize farmers have been at the mercy of a handful of agribusiness giants with the power to dictate the crops to be sown, the livestock to be raised, and the price to be paid for them. Local tax bases have eroded, and with them the services, schools, infrastructure, and other public investments necessary to secure a prosperous future.

More from Nick Hanauer

The American economy continued to expand throughout the neoliberal era, but nearly all of the benefits of this growth accrued to a relatively small number of big cities and their surrounding counties, a trend that only appears to be accelerating. At the median, rural workers now earn only 82 cents on every dollar earned by their urban counterparts, and as rural jobs grow more scarce and less diverse, rural workers have fewer opportunities to close the gap. Nationally, the U.S. workforce grew by 68 percent since 1975 while rural employment actually shrank by nearly a third. Between 2007 and 2018, just 11 percent of counties captured 9 out of every 10 new jobs, a massive concentration of employment and wage growth in a handful of deep-blue metros. In second-tier cities, small towns, and rural counties, the health and well-being of residents are being left behind.

Compared to their urban counterparts, rural Americans are 22 percent more likely to experience poverty, food insecurity (by a 19 percent margin), and to lack health insurance (by 15 percent), contributing to higher rates of depression, addiction, suicide, and other deaths of despair. The COVID-19 virus has shone a particularly harsh light on the consequences of rural economic dislocation. Early in the crisis, cases predictably surged in the dense big cities where community transmission was hardest to avoid. But over the long course of the pandemic, regional socioeconomic disparities conspired with higher rates of obesity, diabetes, hypertension, and other comorbidities to leave rural Americans far more likely to suffer severe illness or death.

If rural voters are angry, they have every right to beand if they look at the relative wealth and good fortune of urban elites and blame their woes on Democratic policies, its not hard to understand why. Yes, there is massive and growing inequality within big blue cities too, but in the aggregate these booming cities are receiving nearly all the benefits of the information economy while rural America reliably gets none. Rural voters are angry, and lacking a more obvious villain they routinely punish Democrats, the party of the cities, at the polls. As the violent rhetoric surrounding the January 6th insurrection indicates, theres a not insignificant number of Republicans who passionately believe that electoral defeat isnt nearly punishment enough.

Rural voters are angry, and lacking a more obvious villain they routinely punish Democrats, the party of the cities, at the polls.

In a truly representative democracy, such extreme geographic inequality would be alarming, but given the peculiar characteristics of the American political system, it threatens to undermine democracy itself. The U.S. Constitution vastly overrepresents small rural states in the U.S. Senate and to a lesser extent in the Electoral College, while a centuries-old tradition of partisan gerrymandering has combined with 21st-century demographics to overrepresent rural voters in state legislatures and in the U.S. House. In nearly every recent election cycle, Democratic candidates routinely receive millions more votes than Republican candidates for the House, the Senate, and the White House, and yet the Republican Party could plausibly establish a regime of minority rule (not to mention a stranglehold on the federal courts) for at least a generation to come. Beholden, both ideologically and financially, to corporate interests, Republican elected officials do little if anything to actually help their rural constituents. Instead, they nurture a politics of grievance. But given the failure of Democrats to offer a compelling alternative, grievance alone appears more than enough for Republicans to continue to secure the rural vote.

President Biden and congressional Democrats have a frighteningly narrow window to persuade a small but electorally significant percentage of rural voters that only Democrats can and will serve their communities needs. To do this, Democrats need to aggressively run on rural revitalization as a centerpiece of their economic agenda in 2022, 2024, and beyond, while immediately using every policy tool at their disposal to begin the difficult work of reversing the extreme geographic inequality that the past 40 years of neoliberalism has wrought.

This should start with the creation of a Cabinet-level director of rural economic revitalization to coordinate the mishmash of existing programs, to guide the development of future policies and programs, and just as important, to serve as the relentlessly visible face of the administrations dedication to improving the lives of rural Americans. To be clear, it is not enough for Democrats to genuinely attempt to solve this problem. It is not even enough for Democrats to succeed. If Democrats are to have lasting success at improving the lives of rural Americans, they must be seen by rural Americans as having success. The first rule of electoral politics is you cant be the grown-up in the room if youre not in the room. Democrats need to get over their preference for highbrow policy wonkery and get about the lowly task of shamelessly advertising their accomplishments for a change.

If you think this is a job for the secretary of agriculture, think again. According to the U.S. Census Bureau fewer than 1 in 10 rural workers are employed in resource-based industries like agriculture, forestry, fishing, hunting and mining, and according to the U.S. Department of Agriculture (USDA), farming itself accounts for only 1.4 percent of employment nationwide. In fact, by far the largest employer of rural workers is the education services, health care and social assistance industry, which accounts for 22.3 percent of rural employment, followed by manufacturing and retail trade, at 12.1 percent and 10.9 percent, respectively. Our tendency to conflate rural with agricultural has made it harder to understand the problems facing rural communities, let alone solve them. The USDA, with its primary emphasis on promoting and regulating the agribusiness and food industries, has neither the focus nor the expertise to rise to the task. Neither do the hodgepodge of other agencies that moonlight in economic development, many of which offer one-size-fits-all programs intended to serve both urban and rural communities alike.

There are literally hundreds of existing policies and programssome of which can and do helpalthough many are chronically underfunded, difficult to access, difficult even to find, and often poorly implemented. A confusingly complex web of programs is currently available to rural communities: There are some 400 economic and community development programs alone that span a dozen federal agencies. There are more than a dozen congressional committees that have jurisdiction over authorizing legislation.

The first job of the director, then, is to identify, consolidate, and coordinate these programs under centralized administration. The second job is to establish and amply staff regional offices nationwide charged with guiding local authorities through the complicated process of navigating the web of available programs. The Small Business Administration and the Economic Development Administration both have networks of regional officesthough all located in urban districts. The federal governments regional revitalization offices should be distributed widely, within driving distance of every rural community, providing one-stop-shopping access to local leaders and constituents alike. It is a well-known weakness of our current system that the communities most in need of federal aid are often those most lacking the resources necessary to acquire it, while those that are most successful at accessing these programs are often those with the least need. It is through these regional revitalization offices that the White House has an opportunity to play its most active, impactful, and again, most visible role.

Yet however competent the administration, more of the same is clearly not enough. Many of the economic-development challenges facing rural economies are fundamentally different from those in large cities and call for a fundamentally different approach. Addressing this crisis at scale requires both big new ideas and the active input and efforts of the local political, business, and civic leaders who know their communities best. To this end, we should balance the top-down Office of Rural Economic Revitalization and its regional offices with the creation of hundreds of local Economic Revitalization Councils. Some will succeed, some will fail. It is the job of the director through the regional offices to nurture, guide, and fund these local efforts, and then to help propagate their most promising innovations to other local councils. Because rural economies are diverse, revitalization will require a diversity of local solutions. This can never be achieved through top-down administration alone, however competent or well-meaning. The ultimate goal of the director is to help local communities revitalize themselves.

Economic-development challenges facing rural economies are fundamentally different from those in large cities and call for a different approach.

That said, our current crisis of geographic inequality is the direct consequence of policy choices made at the national level, and thus the director must also play a leading role in developing and advocating for substantial federal policy reforms. To this end, the local councils can also play an important part, serving as a source, a sounding board, and a political force for national policy innovations.

The job of the director is to lead, not to follow. In his State of the Union address, President Biden twice emphasized that we must grow our economy from the bottom up and from the middle out. Absolutely. But if we are to substantially reverse decades of geographic inequality and the divisive politics it has sown, political leadership, guidance, and funding must come from the top down.

Central to understanding why the challenges facing rural economic development are different from those in cities, as well as the nature of the reforms we must embrace, is to recognize the three major economic forces that are driving geographic inequality: agglomeration, globalization, and corporate concentration.

It is no secret why high-paying tech companies tend to agglomerate in a handful of metro areas: Technological innovation is the product of large numbers of highly educated workers with a huge diversity of specialized skills cooperating across immensely dense social and economic networks. This convergence of density and diversity is an order of magnitude more important than any other factor in our modern technological economy; it creates thick labor markets in which employers can more easily find workers with the skills that exactly fit their needs, and in which workers can find jobs that exactly fit their own career goals and skill sets. Thick labor markets can be expensive, but they are extremely efficient, and they can only develop in and around cities with the scale necessary to support them. No tax incentive, real estate giveaway, or union-busting right to work regime can make up for it. That is why both workers and employers are so eager to pay the high costs required to live and work in a handful of booming blue metros.

Agglomeration is about as close to a force of nature as youll find in economics. It is an increasing returns phenomenon. You cannot effectively legislate for or against it. The same is not true of globalization or corporate concentration, both of which are creatures of the laws, regulations, and institutions we choose to create.

While certainly aided by advances in transportation and communications, the export of U.S. manufacturing jobs to low-wage countries and the relentless downward pressure on the wages of those manufacturing jobs that remain is largely the consequence of neoliberal trade and labor policies adopted since the 1970s. Whatever ones views on the net benefits of globalization, one must still acknowledge that our current regime of free trade is a purely legal constructand that allowing capital and goods to flow freely across borders, while humans remain more rooted to a place, inevitably disempowers workers. Likewise, the vast concentration of corporate power we have allowed to accumulate over the past few decades is a legal construct too, only rather than being a consequence of changes to our antitrust laws, it has largely resulted from the changing legal interpretations of courts and administrations. Prior to the 1970s, our courts and regulators would not allow a handful of companies to dominate an industry through mergers and acquisitions, regardless of the alleged benefits to consumers. Today, such domination is the norm.

The impact of these changes in the legal order on nonurban communities has been particularly devastating. Millions of manufacturing jobs that once supported these regions have moved overseas, while many of those that remain no longer pay middle-class wages. Locally owned businesses that once proudly anchored small towns have been outcompeted or consolidated away. What job growth these regions have seen has largely been in the low-paying service sector dominated by retail and fast-food giants with the market power to force down wages both for their own workers and for those at remaining locally owned businesses. This Walmart Effect is well documented. But so too is the ability of targeted policy changes to combat it.

One of our most effective policy tools is the minimum wage, but rather than relying on a one-size-fits-all lowest-common-denominator approach, it is time to consider a graduated wage in which the largest employers pay a higher minimum. For example, a small locally owned business might be required to pay a $15 hourly minimum wage, while the local Walmart or Amazon warehouse might be required to pay a minimum of $25 an hour. We might think of this as a countervailing wage, intended to countervail the outsized power of these corporate giants on behalf of both local workers and local businesses, both of which recycle money throughout the local economy rather than extracting profits to distant corporate shareholders.

Retail should not be the only target. For example, meatpacking jobs have always been dangerous and difficult work, but for decades they were unionized and paid middle-class wages. Today, four giant meatpacking companies process 85 percent of American beef and have used their market domination to drive down both the wages paid to workers and the prices paid to ranchers, while driving up the cost to consumers and the profits to shareholders. Slaughterhouse and meatpacking jobs are nonexportable; they must be located near the source of the livestock. These companies saw their profit margins jump by a ridiculous 300 percent over the course of the pandemic. There is simply no good economic reason why they cannot pay a middle-class wage once again.

The regional inequity inherent in agglomeration may be the most difficult to effectively address.

A countervailing wage is just one example of the kind of innovative policies we might adopt in the service of revitalizing rural economies. Antitrust enforcement, sectoral bargaining, and a renegotiation of our international trade agreements might do the same. No doubt consumers have benefited greatly from globalization, but at the cost of undermining the resiliency of both our supply chains and our communities. Its past time for policymakers to acknowledge that free trade isnt free. But whatever policies we choose to enact, the fundamental goal should be the same: to tilt the economic playing field back toward local workers and local businesses in the face of the overwhelming forces unleashed by agglomeration, globalization, and corporate concentration.

The regional inequity inherent in agglomeration may be the most difficult to effectively address. The problem for rural economies is that cities are enormously more efficient, and the bigger the city the greater its economies of scale. As the theoretical physicist Geoffrey West has discovered, cities reliably scale, not merely arithmetically, but at a super linear universal exponent of about 1.15. As West explains, that means if you double the size of a cityfrom whatever to twice whateveryou dont just get twice as much of everything you had before, but rather a per capita 15 percent increase in productivity, patents, job categories, wages, and so onalong with a 15 percent savings on per capita energy consumption, roads, utilities, and other infrastructure. Size matters: A city of 200,000 produces 15 percent more patents per person than a city of 100,000, while a city of 3.2 million is roughly 100 percent more innovative, productive, and efficient. And most significant to our growing crisis of geographic inequality, this universal scaling applies to social networks at the same levels it applies to networks of roads, utilities, and other physical things.

This new prosperity is the product of the knowledge and know-how distributed across vastly complex networks of highly cooperative specialists, and these networks of people cannot easily be picked up and moved. These economies of scale, both physical and social, are why Amazons search for HQ2 was largely a scam. It was never going to be located in a small town or second-tier city no matter how affordable the real estate or attractive the tax incentives. The field of realistic sites was always limited to the handful of large metros where the agglomeration effect had already established a thick labor market of information workers, and where the resources existed for this market to grow thicker still. No policy initiative can change this dynamic.

But that does not mean that rural economies cannot create or attract high-paying jobs. During the COVID-19 pandemic, we have seen renewed interest in the potential of remote work, and there are many high-paying job categories that are amenable to at least a hybrid model. This could become a boon for small towns and rural communities as high-earning newcomers spend money into the local economy. But it could also prove a burden on incumbent residents if they get priced out due to the rising cost of housing and other essentials. Our objective is to revitalize rural communities, not places, and so we must be wary of policies and programs that achieve revitalization largely through gentrification and displacement. Accordingly, we must be prepared to address the costs of remote work as well as the benefits.

And where private employers or employees cannot be incentivized to move into rural communities, state and federal governments can. Anchor institutions like public hospitals, libraries, research centersand most famously, land-grant universities and their extension programshave long been prized as engines of economic development, and they could play that role in rural America once again. The USDAs Cooperative Extension System, originally created to serve the needs of farmers and ranchers, should be revitalized and expanded to serve the more diversified needs of our modern rural economies. Of course, rural locations cannot provide the same economies of scale as urban ones, but making their economies more vibrant and viable is a national imperative that taxpayers should be willing to help realize in the service of narrowing geographic inequality and toxic political divisions. And whether public or private, any investment in bringing good jobs to rural communities must be matched with investments in affordable housing, transportation, schools, and other critical infrastructure so that incumbent residents are not disadvantaged or displaced by the inflow of new wealth.

Over the years, task force after task force has been convened by one agency or another to address the economic inequities in the American landscape, but the challenge is too great and the problem too complex to be solved through such an uncoordinated approach. The Biden administration has an opportunity to fix this by appointing a director of rural economic revitalization to lead a coordinated response to one of the greatest political crises of our time. That director will have a narrow window to demonstrate to rural voters that Democrats really are on their side. Democrats dont need to persuade a majority of rural voters, or even a lot of them. Just a few percentage points in a handful of swing states would be enough to block the Trumpist forces from seizing hegemonic minority rule. And that would also give Democrats the breathing space they need to do the hard work necessary to assure that the state of the union between urban and rural America is once again strong.

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Democrats Need to Fix Rural Economiesand Get the Credit for It - The American Prospect

In 1998, Larry Page and Sergey Brin founded the greatest language AI startup of all time. But a new ... [+] generation of challengers is coming.

See here for the first part of this article series: Language Is The Next Great Frontier In AI

Language is at the heart of human intelligence. It therefore is and must be at the heart of our efforts to build artificial intelligence. No sophisticated AI can exist without mastery of language.

The field of language AIalso referred to as natural language processing, or NLPhas undergone breathtaking, unprecedented advances over the past few years. Two related technology breakthroughs have driven this remarkable recent progress: self-supervised learning and a powerful new deep learning architecture known as the transformer.

We now stand at an exhilarating inflection point. Next-generation language AI is poised to make the leap from academic research to widespread real-world adoption, generating many billions of dollars of value and transforming entire industries in the years ahead.

A nascent ecosystem of startups is at the vanguard of this technology revolution. These companies have begun to apply cutting-edge NLP across sectors with a wide range of different product visions and business models. Given languages foundational importance throughout society and the economy, few areas of technology will have a more far-reaching impact in the years ahead.

The first category of language AI startups worth discussing is those players that develop and make available core general-purpose NLP technology for other organizations to apply across industries and use cases.

Building a state-of-the-art NLP model today is incredibly resource-intensive and technically challenging. As a result, very few companies or researchers actually build their own NLP models from scratch. Instead, virtually all advanced NLP in use today, no matter the industry or setting, is based on one of a small handful of massive pretrained language models. Stanford researchers recently dubbed these pretrained models foundation models in recognition of their outsize influence.

Most often, foundation models are built and open-sourced by the publicly traded technology giantse.g., BERT from Google, RoBERTa from Facebook.

OpenAI is another important source of state-of-the-art NLP technology. Its large language model GPT-3 is perhaps the most well-known and widely used foundation model today. GPT-3 is a generative model (the G in its name stands for generative): it generates original text in response to prompts from human users. OpenAI has made GPT-3 commercially available via API for use across applications, charging on a per-word basis.

Given Microsofts massive investments in and deep alliance with the organization, OpenAI can almost be considered an arm of the tech giant.

But there is also tremendous opportunity in this category for younger startups.

Cohere is a fast-growing startup based in Toronto that, like OpenAI, develops cutting-edge NLP technology and makes it commercially available via API for use across industries. Coheres founding team is highly pedigreed: CEO Aidan Gomez is one of the co-inventors of the transformer; CTO Nick Frosst is a Geoff Hinton protg. The company recently announced a large Series B fundraise from Tiger Global less than a year after emerging from stealth.

While Cohere does produce generative models along the lines of GPT-3, the company is increasingly focused on models that analyze existing text rather than generate novel text. These classification models have myriad commercial use cases: from customer support to content moderation, from market analysis to search.

"Language generation has seemingly monopolized the attention of those interested in NLP, but the most significant opportunity for developers interested in building NLP into their systems actually rests in language representation models like BERT, said Gomez. While slightly less 'miraculous', these models form the backbone of some of the most sophisticated NLP systems in the world."

Another leading horizontal NLP startup is Hugging Face. Hugging Face is a wildly popular community-based repository for open-source NLP technology. Unlike OpenAI or Cohere, Hugging Face does not build its own NLP models. Rather, it is a platform that stores, serves and manages the latest and greatest in open-source NLP models, including enabling customers to fine-tune these models and deploy them at scale.

Hugging Faces secret sauce is its community: it has become a go-to destination for companies and researchers in the world of NLP to collaborate. In this respect it can be loosely analogized to GitHub, but for machine learning rather than traditional software engineering.

Other horizontal NLP providers of note include AI21 Labs and Primer.

Based in Israel, AI21 has a two-pronged business model: it offers proprietary large language models via API to power customers applications (its current state-of-the-art model, named Jurassic-1, is roughly the same size as GPT-3), and it also builds and commercializes its own applications on top of those models. Its current application suite focuses on tools to augment reading and writing.

Primer is an older competitor in this space, founded two years before the invention of the transformer. The company primarily serves clients in government and defense.

There is one last wild card worth mentioning in this category. Launched less than a month ago, little is known yet about Inflection AI beyond its eye-catching founding team: Reid Hoffman, DeepMind cofounder Mustafa Suleyman, and decorated DeepMind researcher Karen Simonyan. The company is being incubated at Greylock, where Hoffman is a general partner. Its stated mission is to fundamentally redefine human-machine interaction by enabling humans to relay our thoughts and ideas to computers using the same natural, conversational language we use to communicate with people.

Given the caliber of the companys founders and backers, expect Inflection AI to make waves in the world of language AI before long.

The most basic way that humans use natural language to interface with machines is through search. It is the primary means by which we access and navigate digital information; it lies at the heart of the modern internet experience.

Search has been dominated by a single player for so long (Google) that it is often seen as an unpromising or even irrelevant category for startups. But this is far from true.

Last month a blog post titled Google Search Is Dying made the rounds and sparked widespread discussion. The post hit home with a simple point: an opportunity exists for an upstart to improve and disrupt the Google search experience.

The new entrant taking on Google most directly is You.com. Founded by Richard Socher, former Chief Scientist at Salesforce and one of the worlds most widely cited NLP researchers, You.com is reconceptualizing the search engine from the ground up. Its product vision includes a horizontal layout, an emphasis on content summarization, and above all, a commitment to user data privacy.

Challenging Google directly will, to state the obvious, be an uphill battle. There is also significant opportunity for startups in search beyond the consumer internet search market with which Google has become synonymous.

ZIR AI is a young startup building a new search platform for enterprise. Leveraging the latest transformer-based techniques, ZIR is seeking to develop search technology with true semantic comprehension (as opposed to keyword-based matching) and more sophisticated multilingual capabilities. Like You.com, ZIR has a pedigreed founding team that includes former Cloudera CTO/cofounder Amr Awadallah.

Algolia is a more well-established player in enterprise search; the company has raised over $300 million in venture funding since graduating from Y Combinator in 2014. Algolia offers an API that enables its customersfrom tech companies like Slack to media businesses like the Financial Timesto embed search experiences in their websites and applications. Constructor.io is another fast-growing competitor in this space that focuses specifically on ecommerce search and discovery.

One final enterprise search startup worth keeping an eye on is Hebbia, which is building an AI research platform to enable companies to extract insights from their private unstructured data.

In the words of Hebbia founder/CEO George Sivulka: Google has only indexed 4% of the worlds online data. Were unleashing the other 96%.

All of the companies mentioned above (including Google) focus on text search. But thanks to recent breakthroughs in AI, opportunities now exist for startups to build search tools for data modalities beyond textand no new modality represents a bigger opportunity than video.

Video has become the dominant medium for our digital lives. A whopping 80% of the data on the internet today is video. Yet remarkably, there is no effective way to search through all this video contentto find, say, a particular moment, concept or discussion. The range of potential commercial use cases for video search is basically endless: from social media to streaming content, from digital asset management to workplace productivity, from content moderation to cloud storage.

One exciting startup building next-generation video search capabilities is Twelve Labs, which announced its seed financing earlier this month. Twelve Labs fuses cutting-edge NLP and computer vision to enable precise semantic search within videos. Multimodal AI like thisthat is, AI that ingests and synthesizes data from multiple informational modalities at once, like image and audiowill play a central role in AIs future.

Large language models are accomplishing incredible things today. We think large multimodal neural networks for video are the obvious next step, said Twelve Labs cofounder/CEO Jae Kim. Video embeddings generated by these networks will supercharge current and future video-driven applications with an intelligence that weve never seen before.

In todays information-based economy, perhaps no skill matters more than effective writing.

Yet as anyone who has experienced writers block can attest, writing can be a frustrating experience. The act of translating inchoate thoughts into well-crafted languageof finding the right wordscan be time-consuming and unsystematic.

Next-generation NLP promises to transform how humans write, reconceptualizing one of civilizations most basic and vital activities.

Large language models like OpenAIs GPT-3 can be thought of as auto-complete on (incredibly powerful) steroids. Given some text prompt from a human, these generative models can automatically produce novel sentences, paragraphs or even entire memos that are strikingly coherent, insightful, creativealmost magically so. Of course, their output remains far from perfect: they can also sometimes be nonsensical or harmfully biased.

This technology will transform writing from an act of solo creation to a collaboration between human and machine: one in which the human provides some initial language, the AI suggests edits or follow-up sentences, the human iterates based on the AIs feedback, and so forth. The skillset required for good writing may accordingly expand to include an understanding of how to get the most out of the AIhow to best guide and coax it into producing the desired language.

This novel paradigm for AI-augmented writing is already starting to become a reality, driven forward by a handful of interesting startups.

The most established player in this category is Grammarly. Founded in 2009, Grammarly has admirably remained abreast of the latest NLP technologies over the years. The company raised funding late last year at a whopping $13 billion valuation. Grammarlys product provides automated recommendations for improved spelling, grammar, diction and phrasing in real-time as users write.

Textio, LitLingo, and Writer are three newer entrants using next-generation language AI to build advanced Grammarly-like solutions for more targeted use cases. Textio focuses on hiring and recruiting, LitLingo on business compliance and risk management, and Writer on company-wide style and brand consistency.

Trained on millions of writing samples, Textios AI can give users nuanced insights about their job postings and other hiring-related content: for instance, that a certain phrase will resonate more with male than with female candidates, that a given word suggests a fixed mindset over a growth mindset, that a particular metaphor may come across as exclusionary to applicants. LitLingo, meanwhile, uses real-time NLP to monitor employees digital messages and proactively prevent communications that could trigger litigation or unwanted public attentionsay, related to antitrust, workplace discrimination, securities violations or employment law.

All four of the companies mentioned so far use AI primarily to provide recommendations and insights on existing text that humans have already written. Todays NLP, though, allows us to go one step further. The next frontier in AI-augmented writing will be for the AI to generate novel written content itself based on guidance from the human user.

CopyAI is a Tennessee-based startup backed by Sequoia, Tiger Global and Wing VC that auto-generates customized marketing copy. The way it works is simple. Users enter basic information about their company and select a content format: say, a blog title, a website blurb, a Facebook ad, even an Instagram hashtag. CopyAIs NLP engine, which is powered by GPT-3, then spits out ten samples of text at a time for the user to use, adapt, or take inspiration from. According to the company, over half a million content marketers are using its technology today, including at organizations like Nestle and Microsoft.

To temper expectations, we should not expect that todays NLP will immediately take over all writing from humans. Some forms of writingbrief formulaic content like marketing copy or social media postswill yield more naturally to these new AI tools than will others. Original, analytical, creative worksay, op-eds, thought pieces or investigative journalismwill resist automation for the time being.

But make no mistake: in the years ahead, whether we like it or not, NLP will fundamentally change how humans produce the written word. Ten years from now, writing ones own content from scratch may well be considered an artisanal craft, with the vast majority of the worlds written text produced or at least augmented by AI.

Language barriers are a fundamental impediment to international business and travel, costing untold billions in lost productivity every year.

More profoundly, the inability for people around the world to understand one another inhibits the advancement of grand global goals and species-level harmony. But in a polyglot world like ours (over 7,000 languages are spoken in the world today), language barriers have always been an unavoidable reality.

The Babel fish from Douglas Adams science fiction classic The Hitchhikers Guide to the Galaxywhich goes in someones ear and automatically enables them to hear any spoken language in their native tongueis an enchanting but purely fictional concept.

Until now.

Machine translation has been a central goal of artificial intelligence researchers dating back to the very beginnings of the field of AI in the 1950s. Automated language translation products have been available since the dawn of the commercial internet in the 1990s. Yet machine translation has proven to be a devilishly difficult challenge. AI-based translation tools have historically been deeply flawed (as anyone who remembers using AltaVistas Babel Fish service in their younger days can attest).

But thanks to the remarkable advances underway in language AI, reliable and high-quality machine translation is fast becoming a reality.

The most widely used AI-powered language translation service in the world is Google Translate. Unsurprisingly, given that it is the birthplace of the transformer and the most advanced AI organization in the world, Google has incorporated the latest NLP technologies to vastly upgrade its Translate service in recent years.

But significant opportunities also exist for startups in the fast-changing world of language translation.

BLANC offers AI-powered translations for video. Its AI platform takes a video with spoken dialogue in one language and applies AI to quickly reproduce that video with the dialogue in another language, doing so in a way that the speakers lip movements continue to look natural. Think of it as sophisticated dubbing, except that it can be carried out automatically and at scale.

KUDO is a more established competitor that also offers video translation services. Today, KUDOs platform relies on human interpreters to stream translations over the internet in real-time. But the company envisions a future in which its platform is increasingly powered by AI. In this sense KUDO represents an interesting archetype: a mature non-AI-first business looking to inject more AI into its product offering by leveraging its massively valuable proprietary datasets.

Lilt is a notable growth-stage player working on machine translation. The company was founded by two NLP researchers at Google Translate who came to appreciate that an AI solution like Google Translate could not, on its own, be relied upon to deliver automated language translation with the robustness demanded by enterprise and government organizations.

Thus, Lilt offers a hybrid model that combines cutting-edge AI with humans in the loop to translate written content for global organizations, from marketing to mobile apps to technical documentation. This partially automated approach enables Lilt to provide translation that is cheaper than using human translators and at the same time more accurate than using AI alone.

The interesting questionfor Lilt and for the entire industryis whether and how quickly the humans in the loop can be phased out in the years ahead.

One last startup worth mentioning in this category is NeuralSpace. NeuralSpace was founded on a simple but powerful insight: the vast majority of cutting-edge research in NLP is conducted in English, yet 95% of the world does not speak English. NeuralSpace provides a no-code NLP platform that enables users around the world to build NLP models in low-resource languages, from Armenian to Punjabi to Zulu.

Our vision at NeuralSpace is to break down the language barrier in AI for millions of low-resource language speakers, said NeuralSpace cofounder/CEO Felix Laumann. We give software developers the ability to train and deploy state-of-the-art large transformer-based language models and easily integrate them into their products, no matter where in the world they are or what language their audience speaks.

Sales is more of an art than a science. Yet certain repeatable principles and tactics do exist that, if systematized, can meaningfully improve a sales teams performance.

Is a rep spending the right amount of time on the right topics in sales calls, from product to pricing to small talk? Is she letting the customer ask enough questions? Has she engaged the right senior stakeholders at the customer organization at the right times over the course of the sales process? Is she following up with prospects on the right cadence?

By ingesting vast troves of unstructured data from video calls, phone calls, email exchanges, CRMs and other communication channels, todays language AI can extract actionable insights about how salespeople are performing and what they can do to improve.

There are few applications of language AI that can more directly affect a companys top line. Not surprisingly, therefore, the market for sales intelligence AI is booming.

The runaway leader in this category is Gong, which has raised close to $600 million in venture funding. According to the company, its technology boosts average revenue per sales rep by 27%, translating into massive ROI for its customers.

Gongs closest competitor Chorus.ai exited to ZoomInfo last year in a $575 million sale, further solidifying Gongs status as the category leader.

Gong is an impressive business, with incredible revenue growth and a long list of blue-chip customers. The company seems destined to debut on public markets before long. Yet by most accounts, the core NLP in Gongs product offering is not particularly advanced.

This raises an interesting question: might an opportunity exist for an upstart to build a more cutting-edge version of Gong, powered by the latest transformer-based advances in language AI, and take market share from the category leader by offering a more intelligent product?

A handful of young startups have popped up that are nipping at Gongs heels, though none have yet broken out.

Aircover, which raised a seed round last year, and Wingman, which came out of Y Combinator in 2019, are two examples. Unlike Gong, which provides analytics only after sales calls are finished, both of these startups provide real-time in-call coaching for sales reps. And while Gong has had major success selling to large enterprises, Wingman instead targets small- and medium-sized businesses.

We all experience it in our daily lives: when we communicate digitally with companies and brands these daysvia text message, web chat, social media, and so forththese interactions are increasingly fielded by automated agents rather than humans.

These AI-powered conversational interfaces are commonly known as chatbotsthough some startups today prefer to avoid that terminology and its mixed connotations, given a premature hype cycle for chatbot technology about five years ago.

Notwithstanding earlier false starts, chatbots today have begun to gain real market adoption, thanks to improvements in the underlying NLP as well as in companies understanding of how to best productize and deploy these bots.

Companies are now using chatbots to engage with customers in real-time wherever those customer interactions occurfor instance, fielding questions on their websites, automating routine customer support requests, giving customers updates on their orders, or supporting sales efforts.

Most organizations interested in using conversational AI interfaces to interact with their customerssay, a bank, a hotel chain, an airlinelack the requisite technical resources to navigate the latest NLP technologies and build their own chatbot platforms from scratch.

And a lot goes into building an enterprise-grade conversational AI interface: handling data privacy and security requirements, integrating with third-party applications, building the infrastructure to support deployment at scale, providing a graceful fallback mechanism when the bot is stumped and human intervention is necessary.

A promising group of startups has emerged to provide the technology and infrastructure for companies across industries to create and operationalize chatbots.

The most well-funded of these competitors is Ada Support, a Toronto-based startup that has raised close to $200 million from blue-chip venture capitalists. Ada powers automated interactions for enterprises in customer support and sales across text-based channels including web chat, SMS, and social media, intelligently looping in a human agent when needed. The company claims its technology can reduce customer wait times by 98%. With a long list of marquee clients including Zoom, Shopify, Verizon and Facebook, Ada powers over one billion customer interactions annually.

Another leading player in this category is Rasa. A close Ada competitor, Rasas product caters to more technically savvy users, with a greater focus on chatbot configurability. Rasas AI stack is open-sourced, with over 600 contributors and over 10 million downloads. This open-source strategy gives Rasas customers greater transparency and control over the conversational AI interfaces that they build and deploy.

Other noteworthy startups in this space include Forethought, a well-capitalized competitor that boasts NLP luminary Chris Manning as an adviser; Clinc, a conversational AI platform built specifically for banks; and Thankful, which focuses on e-commerce.

One specific type of enterprise chatbot has proven to be a sufficiently large market opportunity that it gets its own section: chatbots to automate employee help desks.

Every day, in every company around the world, employees have routine questions that they need help with: how to reset their email password, whether they can expense an enterprise software subscription, how to enroll in a health insurance plan, what the companys vacation policy is.

Conversational AI platforms can automatically field and resolve many of these employee support requests, reducing the need for human intervention and saving organizations vast amounts of time and money in the aggregate.

The leading player in this category is Moveworks, which raised a $200 million Series C from Tiger Global last year. Another well-funded competitor is Espressive. Espressive claims that its chatbot platform can resolve between 50% and 70% of all employee helpdesk tickets without human assistance, recouping over a week of productivity per employee per year.

Given the size of the market, plenty of smaller startups have emerged with similar AI-driven product offerings. One worth noting is Bay Area-based Rezolve.ai.

When Google debuted its new Duplex technology in mid-2018, it wowed the public (and generated its fair share of controversy).

Duplex is an AI system that, in a remarkably human-sounding voice, can place phone calls on behalf of human users to complete routine tasks like booking a dinner reservation or a hair appointment.

At the time, Googles Duplex was just a demo, still heavily reliant on human-in-the-loop support.

Four years later, this technology is ready for primetime.

Following in Duplexs footsteps, a handful of startups have developed voice AI technology that can engage in nuanced automated phone conversations. While Googles Duplex is a consumer-facing tool (it is widely available today through apps like Google Maps), these startups go-to-market efforts focus on the enterprise. And no enterprise opportunity looms larger for this technology than contact centers.

Contact centers (also referred to as call centers) are an unglamorous back-office function that happen to also be a staggeringly massive marketan estimated $340 billion in 2020, on its way to $500 billion by 2027.

Replicant is one promising startup applying voice AI to automate contact center agent activity, reducing wait times for customers and cutting costs for companies. Replicant spun out of Atomic, the high-profile startup studio that has produced companies like Hims and OpenStore.

Like Duplex, Replicants voice AI is designed to sound as natural as a human (the companys name is a tribute to the bioengineered robots from Blade Runner that are indistinguishable from humans). Replicants technology is equipped to handle a wide range of call center use cases, from billing to customer surveys to subscription renewals. When its AI encounters a complex conversation topic that it cannot resolve on its own, it pulls in a human agent.

A close Replicant competitor is AI Rudder, a Singapore-based company that just raised $50 million from Sequoia, Coatue and Tiger Global.

AI Rudder sells to customers in financial services and e-commerce, two industries that make extensive use of call centers. The pandemic has driven rapid growth for AI Rudder, whose revenue quadrupled last year. The companys AI system can not only speak a wide range of different languages but can also adopt the appropriate regional accent depending on the caller.

One last startup of note in this category is Resemble AI, which specializes in generating realistic human voices using generative adversarial networks (GANs). Resembles synthetic voices can speak with all the nuance and range of a humanfor instance, whispering or communicating with various emotionsand are finding use cases from video games to advertising. The company recently made headlines when its technology was used to reproduce Andy Warhols voice for an upcoming Netflix documentary.

As the previous section highlighted, contact centers are a massiveand massively underdigitizedmarket. There is tremendous opportunity to transform the world of contact centers with software and machine learning.

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A Wave Of Billion-Dollar Language AI Startups Is Coming - Forbes

LINCOLNVILLE The Wildlife Workshop will be held on April 19, 2022, at the 4-H Camp and Learning Center at Tanglewood, in Lincolnville, and on April 22, 2022 at the Sportsmans Alliance of Maine in Augusta. Youth ages 9 to 19 who are interested in learning more about Maine wildlife and habitats can attend either workshop.

Activities include examining animal pelts and skulls, tree identification, and lots of time outdoors. Teen participants will delve deeper into ecological concepts and discuss potential career paths. All participants will also learn about how to get involved in 4-H and the Wildlife Habitat Education Program.

The workshop is free, but spaces are limited, so please be sure you can commit to attending before registering, said University of Maine Cooperative Extension, in a news release. You do not need to be enrolled in 4-H to participate.

Visitextension.umaine.edu/York/4-h/programs-and-events/to register, or contact Erin McDonald aterin.mcdonald1@maine.eduor 207-324-2814 for more information.

University of Maine Cooperative Extension:

As a trusted resource for over 100 years, University of Maine Cooperative Extension has supported UMaine's land and sea grant public education role by conducting community-driven, research-based programs in every Maine county. UMaine Extension helps support, sustain, and grow the food-based economy. It is the only entity in our state that touches every aspect of the Maine Food System, where policy, research, production, processing, commerce, nutrition, and food security and safety are integral and interrelated. UMaine Extension also conducts the most successful out-of-school youth educational program in Maine through 4-H.

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4-H Wildlife Workshop to be held in Lincolnville - PenBayPilot.com

The Mad River Valley Recreation District and community partners will receive a $408,019 Vermont Outdoor Recreation Collaborative (VOREC) grant to develop a recreation hub that links recreation trails to Waitsfield and Irasville.

The grant is the largest VOREC grant that the Vermont Department of Forests Parks and Recreation awarded last week. The rec district application was one of 104 initital letters submitted and one of the 37 that were invited to submit a full application. Thirty complete applications were received requesting $7.1 million. Vermont had $5.1 million to award and awarded $4,546,813 to 24 towns/projects. Grant amounts ranged from the rec districts $408,019 to $62,500 for the town of Cabot.

"The successful VOREC grant application represents one of the largest investments in outdoor recreation in the history of the Mad River Valley. It will provide a focal point for visitors and residents to access, learn about and enjoy our recreational assets. The recreation hub will offer additional downtown parking, restrooms and be strategic in how it ties our trail infrastructure to our business community. The collaboration between all the partners has been tremendous and the Mad River Valley Chamber of Commerce is honored to be involved, said Eric Friedman, executive director of the Mad River Valley Chamber of Commerce.

BRIDGE OVER MILL BROOK

The recreation hub will be developed at Localfolk Smokehouse, on Route 17, where parking, restrooms and a welcome center will be located. The hub will include a bridge over the Mill Brook (thanks to easements with private landowners) connecting to the existing Mad River Riders 60-plus-mile trail network in the Howe Block of Camels Hump State Forest with Waitsfields commercial center. It will also provide a Valley-to-mountain recreation corridor and include a crosswalk over Route 100 and new section of Mad River Path providing a safe way for pedestrians and bikers to get to restaurants and shops.

"Much progress has been made over the past several months to establish the best way possible for connecting pedestrians and people on bikes between the new recreation hub and downtown Irasville. The Mad River Path and Waitsfield are working closely with VTrans to finalize the fine details that will allow for this off-road connection to be a safe and effective route for anyone on foot or bicycle, said Ross Saxton, executive director of the Mad River Path.

"This project continues years of work that is making downtown Waitsfield and Irasville a safer and more fun place to walk, roll or ride a bike. Connecting our downtown to the businesses, amenities, recreation sites and living spaces that have been just out of safe reach for pedestrians and bikers is a huge step for our community's vibrancy. When construction is complete, we'll be able to enjoy a much better-connected downtown, continued Saxton.

The new roadside trail along Route 100 will extend about 1/4 mile from Mad River Valley Real Estate building, up Dugway Road, across the hillside below The Blue Stone, and along Route 100 to the upcoming Addison West shop (formerly The Store). The surface will be a state-approved aggregate that meets accessibility specifications. Two Route 100 crosswalks are being planned with VTrans to help people cross the road; the first crosswalk location is planned between the new Recreation Hub site behind Localfolk to the MRV Real Estate parking area, and the second crosswalk is planned between the new Addison West shop (formerly The Store) and next to Northfield Savings Bank.

ENVIRONMENTAL STEWARDSHIP

A key component of the project is the fact that it will be built in accordance with environmental protection measures including erosion control, runoff mitigation and an enhanced riparian buffer. Environmental stewardship is a core focus through project design, community engagement in trail visioning and educational initiatives, the applicants wrote in the grant proposal.

Our Mad River Valley community loves being active outdoors and loves nature, said Corrie Miller, executive director of Friends of the Mad River. Im looking forward to the opportunity to dream together as a community about how the Valleys trail network can capitalize on outdoor recreational benefits while also sustaining and enhancing the ecological integrity of the watershed so that future generations can enjoy it.

Increasing stewardship of outdoor recreation resources and environmental quality is one of the five critical pillars of the VOREC grant. Other pillars include increasing participation in outdoor activities for all demographics, strengthening the quality and extent of outdoor resources, growing outdoor recreation-related businesses and promoting the benefits of outdoor recreation.

TRAIL-BASED RECREATION

The Mad River Recreation Hub will expand the economic and social impact of outdoor recreation in the Mad River Valley by capitalizing on existing recreation assets and community initiatives. There are 185 miles of mapped public recreational trails in The Valley (Catamount Trail, Long Trail, VAST Trails, as well as local trails). The demand for trail-based recreation and its importance to the local economy has led project partners to work together for the past decade to improve The Valleys trail network.

Building on the MRV Moves Plan and the Forest, Wildlife Communities Projects, The Valleys conservation commissions, Friends of the Mad River and the MRV Trails Collaborative are working together to better incorporate landscape-level natural resource values into regional trail planning. The partners envision a Gold Standard trail network for The Valley that grows and sustains outdoor recreation and off-road connectivity for all their health, education and economic benefits, while enhancing the ecological integrity of the local watershed.

DIRECT LINKS

The Mad River Riders have been building and protecting trails for public use since 1986. The bridge over the Mill Brook will link directly to the heart of The Valleys trail network. People can gather at the hub and head out into the woods for a loop through the forest or a longer journey. Then back into town for a meal or beer without moving their cars. The trails link directly to Lareau Swim Hole, Riverside Park, more than a dozen inns, Fayston Elementary School, Sugarbush snowmaking pond, Eurich Pond, Lincoln Peak, Mount Ellen and many other places, said Bob Kogut, president of the Mad River Riders.

We have a strong team that brings a depth of experience to this project and reflects The Valley's unique potential and values," said Laura Arnesen, executive director of the Mad River Valley Recreation District.

This project capitalizes on a history of collaboration between local planning, recreation and environmental groups and builds on recent data showing the economic impact of trail-based recreation. Taxpayer support for the rec district's executive director position, which I now hold, enabled us to provide administrative support for this project. Every member of our team has played a critical role in helping us get the largest VOREC grant in Vermont this year. Its a two-year project so there is much work ahead. We appreciate the support and look forward to working with the community to achieve this new recreation hub in downtown Waitsfield, concluded Arnesen.

Expect a late April or early May community conversation about the new recreation hub that mirrors one held last November about the project.

Governor Phil Scott will announce all recipients of the VOREC grants at a press conference in Danville on Monday, March 28, at 11 a.m.

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MRVRD to receive $408, 019 VOREC grant - The Valley Reporter