Page 2,827«..1020..2,8262,8272,8282,829..2,8402,850..»

Will Artificial Intelligence Robots Do the Majority of Our Work in the Coming Decade? – BBN Times

Artificial intelligence robots are slowly replacing blue collar and white collarworkers.

Go to the trading floors to find out that there are no human brokers. Algorithmic trading software makes money for most investment funds.

It takes 0.2 seconds for a price quote to come from the exchange to your software vendors data center (DC), 0.3 seconds from the data center to reach your trading screen, 0.1 seconds for your trading software to process this received quote, 0.3 seconds for it to analyze and place a trade, 0.2 seconds for your trade order to reach your broker, 0.3 seconds for your broker to route your order to the exchange.

Total time elapsed = 0.2 + 0.3 + 0.1 + 0.3 + 0.2 + 0.3 = 1.4 seconds. In todays dynamic trading world, the original price quote would have changed multiple times within this 1.4 second period. The algorithmic trading program is to identify profitable opportunities and place the trades to generate profits at a speed and frequency that is impossible to match by a human trader.

No chance for humans to compete with machines in computing speed and efficiency, instant analysis and decision-making.

The human-AI replacement process is following the causal link of smart work automation:

Office workers -> Distant workers -> RPA bots -> Digital workers -> AI workers

"A digital worker is software designed to model and emulate human job roles by performing end-to-end job activities using automation and AI-based skills. In contrast, an RPA bot is software that mimics human actions by performing specific tasks for which its programmed.

Digital workers can understand, decide and act to automate job roles as opposed to simply acting to automate individual tasks. In doing so, they extend RPA capabilities and can be applied to more use cases". IBM DW

The human-robot replacement has been accelerated by COVID-19. Google as Facebook let their employees continue to work from home through July 2021 due to the ongoing COVID-19 pandemic. Most of them will hardly return back.

As McKinsey cautiously projected:

"The activities most susceptible to automation are physical ones in highly structured and predictable environments, as well as data collection and processing.

In the United States, these activities make up 51 percent of activities in the economy, accounting for almost $2.7 trillion in wages.

They are most prevalent in manufacturing, accommodation and food service, and retail trade. And its not just low-skill, low-wage work that could be automated; middle-skill and high-paying, high skill occupations, too, have a degree of automation potential".

View post:
Will Artificial Intelligence Robots Do the Majority of Our Work in the Coming Decade? - BBN Times

Read More..

This is Why Miners are Investing in Artificial Intelligence – Baystreet.ca

Mining has become essential. With a growing population, urbanization, demand for green energy, buildings, cars, and even more electronic gadgets, well see an increased need for metals. What makes mining even more valuable is the fact were already coming up short on necessary metals, like copper, silver, platinum, palladium, nickel, cobalt, and rhodium to name a few. Thats just part of the reason investors may be pouring money into the red hot mining sector, fueling potential upside for companies such as Windfall Geotek Inc. (TSXV:WIN) (OTC:WINKF)(FSE:L7C2), Emerita Resources Corp. (CVE:EMO)(OTC:EMOTF), Labrador Gold Corp. (TSXV:LAB)(OTC:NKOSF), Eskay Mining Corp. (TSXV:ESK)(OTC:ESKYF), and Goldshore Resources Inc. (TSXV:GSHR)(OTC:SMDXD).

In addition, The mining industry is seeing an increase in artificial intelligence (AI) investment across several key metrics, according to an analysis of GlobalData data, as noted by Mining Technology. Plus, according to PreScouter, McKinseyestimates that by 2035, the age of smart mining achieved through autonomous mining using data analysis and digital technologies like artificial intelligence (AI) willsave between $290 billion and $390 billion annually for mineral raw materials producers. Thats beneficial for companies like Windfall Geotek, which is providing artificial intelligence (AI) to unearth minerals with a higher likelihood of success.

Windfall Geotek Provided AI Gold Target to Dios Exploration on K2 Project in Quebec

Windfall Geotek (TSXV:WIN; OTCQB:WINKF), a leader in the use of Artificial Intelligence (AI) with advanced knowledge-extraction techniques since 2005 in the mining sector is pleased to announce that it will provide and AI Gold target on Dios Exploration K2 project located in the Eeyou Istchee James Bay region of the province of Quebec.

Dinesh Kandanchatha, Chairman of Windfall Geotek commented: We are pleased to announce this agreement with Dios Exploration where we are able to take advantage of our history of work in that region having done the Elmer project in the past which has had positive results. We are excited to be working with Dios Exploration in a Win-Win scenario at a strategic time with the upcoming field work Dios is undertaking over summer 2021.

Marie- Josee Girard, President & Geologist of Dios Exploration Inc commented: We are thrilled to have acquire this high probability target ahead of our Summer 2021 campaign in the area, we have seen positive results with our neighbour in the same geological context and we feel this target as good potential.

Other related developments from around the markets include:

Emerita Resources Corp. announced that it has received a resolution from the Mining Department in Huelva approving the proposed work program for the entire Iberia Belt West project, subject to the Company receiving final approval from the Environmental Department for the El Cura and La Romanera targets. Emerita has engagedFRASA Ingenieros Consultores, a highly reputable engineering firm with offices in Spain and internationally, to prepare the environmental documentation for the west side of the IBW project, including the El Cur and La Romanera targets, in order to obtain the Autorizacion Ambiental Unificada (AAU). FRASAare the environmental consultants used by major companies in the area for permitting and are well versed in the requirements to obtain work permits.

Labrador Gold Corp. announced another high-grade intercept of near surface gold mineralization from its Kingsway project near Gander, Newfoundland. The Kingsway project is located in the highly prospective central Newfoundland gold belt.The high-grade intersection is from hole K-21-17 that contains fine particles of visible gold in quartz vein. The hole intersected 50.38 g/t Au over 1.85 metres including 160.42 g/t over 0.55 metres. The quartz vein containing the visible gold is typically vuggy and locally contains stylolites and is similar to quartz veins containing high grade gold intersections of 20.6 g/t Au over 3.6 metres including 103.36 g/t over 0.3 metres and 10.48 g/t Au over 2.4 metres reported previously.

Eskay Mining Corp. announced that it has commenced its 2021 exploration program with a property wide SkyTEM Survey across its 100% owned Consolidated Eskay precious metal-rich volcanogenic massive sulphide project in the Golden Triangle, British Columbia. SkyTEM is a powerful helicopter supported electromagnetic technique that differentiates electrically resistive and conductive rocks in the subsurface. It is particularly helpful in recognizing areas of relatively conductive altered and sulphide-bearing rocks associated with stockwork VMS mineralization.

Goldshore Resources Inc. announced that it has received its exploration permit from the Ministry of Energy, Northern Development and Mines, allowing the Company to commence its drilling activities at the Moss Lake Gold Project. Brett Richards, President and Chief Executive Officer commented: "I am pleased to have received our exploration permit as it is one of the first milestones we have set for the Company, and allows us to commence our planned100,000 mdrill program as part of a larger exploration strategy that will last close to 24 months."

Legal Disclaimer / Except for the historical information presented herein, matters discussed in this article contains forward-looking statements that are subject to certain risks and uncertainties that could cause actual results to differ materially from any future results, performance or achievements expressed or implied by such statements. Winning Media is not registered with any financial or securities regulatory authority and does not provide nor claims to provide investment advice or recommendations to readers of this release. For making specific investment decisions, readers should seek their own advice. Winning Media is only compensated for its services in the form of cash-based compensation. Pursuant to an agreement Winning Media has been paid three thousand five hundred dollars for advertising and marketing services for Windfall Geotek by Windfall Geotek We own ZERO shares of Windfall Geotek. Please click here for full disclaimer.

Contact Information: 2818047972[emailprotected]

Read the original post:
This is Why Miners are Investing in Artificial Intelligence - Baystreet.ca

Read More..

Can artificial intelligence predict how sick you’ll get from COVID-19? UC San Diego scientists think so – The San Diego Union-Tribune

A team of San Diego scientists is harnessing artificial intelligence to understand why COVID-19 symptoms can vary dramatically from one person to the next information that could prove useful in the continued fight against the coronavirus and future pandemics.

Researchers pored through publicly available data to see how other viruses alter which genes our cells turn on or off. Using that information, they found a set of genes activated across a wide range of infections, including the novel coronavirus. Those genes predicted whether someone would have a mild or a severe case of COVID-19, and whether they were likely to have a lengthy hospital stay.

A UC San Diego-led team joined by researchers at Scripps Research and the La Jolla Institute for Immunology published the findings June 11. The studys authors say their approach could help determine whether new treatments and vaccines are working.

When the whole world faced this pandemic, it took several months for people to scramble to understand the new virus, said Dr. Pradipta Ghosh, a UCSD cell biologist and one of the studys authors. I think we need more of this computational framework to guide us in panic states like this.

The project began in March 2020, when Ghosh teamed up with UCSD computer scientist Debashis Sahoo to better understand why the novel coronavirus was causing little to no symptoms in some people while wreaking havoc on others.

There was just one problem: The novel coronavirus was, well, novel, meaning there wasnt much data to learn from.

So Sahoo and Ghosh took a different tack. They went to public databases and downloaded 45,000 samples from a wide array of viral infections, including Ebola, Zika, influenza, HIV, and hepatitis C virus, among others.

Their hope was to find a shared response pattern to these viruses, and thats exactly what they saw: 166 genes that were consistently cranked up during infection. Among that list, 20 genes generally separated patients with mild symptoms from those who became severely ill.

The coronavirus was no exception. Sahoo and Ghosh say they identified this common viral response pattern well before testing it in samples from COVID-19 patients and infected cells, yet the results held up surprisingly well.

It seemed to work in every data set we used, Sahoo said. It was hard to believe.

They say their findings show that respiratory failure in COVID-19 patients is the result of overwhelming inflammation that damages the airways and, over time, makes immune cells less effective.

Stanfords Purvesh Khatri isnt surprised. His lab routinely uses computer algorithms and statistics to find patterns in large sets of immune response data. In 2015, Khatris group found that respiratory viruses trigger a common response. And in April, they reported that this shared response applied to a range of other viruses, too, including the novel coronavirus.

That makes sense, Khatri says, because researchers have long known there are certain genes the immune system turns on in response to virtually any viral infection.

Overall, the idea is pretty solid, said Khatri of the recent UCSD-led study. The genes are all (the) usual suspects.

Sahoo and Ghosh continue to test their findings in new coronavirus data as it becomes available. Theyre particularly interested in COVID-19 long-haulers. Ghosh says theyre already seeing that people with prolonged coronavirus symptoms have distinct gene activation patterns compared to those whove fully recovered. Think of it like a smoldering fire that wont die out.

The researchers ultimate hope isnt just to predict and understand severe disease, but to stop it. For example, they say, a doctor could give a patient a different therapy if a blood sample suggests theyre likely to get sicker with their current treatment. Ghosh adds that the gene pattern theyre seeing could help identify promising new treatments and vaccines against future pandemics based on which therapies prevent responses linked to severe disease.

In unknown, uncharted territory, this provides guard rails for us to start looking around, understand (the virus), find solutions, build better models and, finally, find therapeutics.

More:
Can artificial intelligence predict how sick you'll get from COVID-19? UC San Diego scientists think so - The San Diego Union-Tribune

Read More..

DeepMind wants to use its AI to cure neglected diseases – Wired.co.uk

In November 2020, Alphabet-owned AI firm DeepMind announced that it had cracked one of biologys trickiest problems. For years the company had been working on an AI called AlphaFold that could predict the structure of proteins a challenge that could prove pivotal for developing drugs and vaccines, and understanding diseases. When the results of the biennial protein-predicting challenge CASP were announced at the end of 2020, it was immediately clear that AlphaFold had swept the floor with the competition.

John Moult, a computational biologist at the University of Maryland who co-founded the CASP competition, was both astonished and excited at AlphaFolds potential. It was the first time a serious scientific problem had been solved by AI, he says. The prospect of having high quality computed structures for most proteins will be a terrific help in understanding many aspects of biology. For example, next time we have a pandemic, we could much more rapidly identify possible drug strategies.

Earlier in 2020, predictions released by AlphaFold at the beginning of the Covid-19 pandemic provided a little hint of what was to come. In late January, DeepMinds scientists used the program to map out a number of the Sars-CoV-2 virus proteins predictions which were later experimentally confirmed to be accurate. This information was then used by virologists around the world, as they scrambled to understand how the virus was behaving.

Now 18 months on, DeepMind is moving on to more real-world applications for AlphaFold. The company has just announced a new partnership with the Geneva-based Drugs for Neglected Diseases initiative (DNDi). DNDi is a non-profit pharmaceutical organisation which has spent the last 18 years attempting to tackle some of the most deadly diseases in the developing world, sleeping sickness, Chagas disease, and Leishmaniasis.

It is the latter two diseases where DNDi hopes that AlphaFold can make the biggest difference. It has already had considerable success in finding new treatments for sleeping sickness. Most notably, it has replaced melarsoprol a toxic compound which killed one in 20 patients with the safe drug fexinidazole, as the new standard of care for the disease.

We went from something that was awful to something thats completely safe, and works in all forms of the disease, says Ben Perry, a medicinal chemist and project leader at DNDi. And in two years time, we hope to have a single dose cure. But unfortunately for Chagas disease and Leishmaniasis, this strategy hasnt worked.

This is because some parasites are particularly resilient. In particular, for Chagas disease a life threatening illness which can lead to heart failure, and affects between six and seven million people, predominantly in Latin America curing the patient requires eliminating every last microorganism from their cells.

Over the past 18 months, DNDi and a team of infectious disease researchers at the University of Washington, University of Dundee, and GlaxoSmithKline, have identified a molecule which appears to be capable of binding to a protein on Trypanosoma cruzi, the parasite that causes Chagas disease. This enables it to shut down the parasite and kill it.

These scientists want to study this proteins structure to understand exactly how the drug is stopping the parasite from functioning. In the past this would have been a complex and laborious experimental task, taking many years, but through AlphaFold, DNDi and their collaborators have already received a computationally-generated prediction of its shape. Perry hopes that this knowledge could now be used to design more drugs which can bind to this protein in different ways, and kill Trypanosoma cruzi.

This could allow us to crack Chagas disease and Leishmaniasis a lot more quickly than it looked like we were going to be able to do a couple of years ago, says Perry. If you can quickly get these protein structures, you can design multiple drug candidates, so you have lots of shots on goal for clinical trials.

Excerpt from:
DeepMind wants to use its AI to cure neglected diseases - Wired.co.uk

Read More..

Are toxins flushed out of the brain during sleep? – Harvard Health

Q. Ive heard that toxins are flushed out of the brain during sleep. Is that true?

A. One of the most interesting discoveries in the past decade is that the brain has a "waste management system." Like people, in order to have the energy to do their work, brain cells need to eat (to absorb, primarily, sugar and oxygen). And, as in people, meals lead to wastes that need to be disposed of. The waste management system (called the glymphatic system) is a series of tubes that carry fresh fluid into the brain, mix the fresh fluid with the waste-filled fluid that surrounds the brain cells, and then flush the mix out of the brain and into the blood. This occurs primarily during deep sleep.

There is some evidence that an under-functioning waste management system may play a role in the neurodegeneration that follows traumatic brain injury (as experienced by some football players, for example). It may even play a role in other brain disorders, including Alzheimers disease. Since chronic sleep deprivation increases the risk for various brain diseases, it is plausible that it does so by reducing the function of the waste management system.

Why do we sleep? We know it helps to rest the body and to consolidate memories and learning. Perhaps we also need to sleep to flush wastes from our brain.

Anthony L. Komaroff, M.D.Editor in Chief, Harvard Health Letter

As a service to our readers, Harvard Health Publishing provides access to our library of archived content. Please note the date of last review or update on all articles. No content on this site, regardless of date, should ever be used as a substitute for direct medical advice from your doctor or other qualified clinician.

See the original post:
Are toxins flushed out of the brain during sleep? - Harvard Health

Read More..

Shame in Medical Training, and Owning Our Stories – Medscape

In last week's blog post, I wrote a line that's been stuck in my mind: "Shame, the ever-present companion of medical culture, once again getting in the way of an honest conversation."

Shame wasn't the main topic of that piece, but I think my subconscious was telling me I needed to write more on it. I thought of Dr Rana Awdish's powerful memoir, In Shock. In it, she writes, "Medicine is not oriented to recognize trauma in its own...We were trained to leave the thin veneer covering our colleagues' emotions undisturbed. We have utterly no idea what to do with shame. We have built no confessionals."

For many (if not most) physicians, the mistakes we make, even minor ones, stay with us for the rest of our careers. As Dr Awdish writes, "That shame is unique in its wholeness, an impenetrable black orb that deflects light."

For some of us who write, the blank page (or screen) is our confessional. This month marks 20 years since completing my internship. There are so many memories from that intense year when I made the transition from student to doctor. But like many of us (I suspect), one of the memories that predominates is of a mistake I made. Not only the mistake but the shame that came with it. So here is my confession, one I've never shared before.

* * *

It's a typical call night on the internal medicine service. I've admitted a woman in her sixties with ESLD and ascites. She's frail, looks 10 years older than her age, and her thin arms and legs jut out in skeletal contrast to her protuberant belly. We're admitting her for a "tap," a paracentesis. Unfortunately, it's late, probably around 11 PM, before my resident and I have enough time between admissions to do the procedure.

I gather the supplies and bring everything to the bedside. Back then we did them without ultrasound, by anatomic landmarks only. I prep everything in the room and go to grab my senior resident. He's at the nurses' station on a computer. "You go ahead," he says, without turning around. "I'll be out here if you need me."

I stand still for a minute. I've done a few by this point. I've graduated past the "see one, do one, teach one" to having done one, and then several, although I haven't yet taught it to anyone. But my resident is busy and showing his trust in me. I can do this. Okay.

I go back into the room. My patient signed the consent already. She's had this done before many times, and she doesn't appear anxious, only tired. I prep the site, numb it up, insert the needle, and am rewarded with the straw-colored fluid I expect to see.

A flash of pride fills me. In hindsight, I should have known better. I hook the catheter up to the needle and connect it to the vacutainer bottle, and we make small talk as the bottles fill. When it looks like we've got all we're going to, I remove the needle and press a gauze over the site.

She cries out in pain. "What are you doing?"

I explain that the needle's out and I'm holding pressure on the site before I bandage it.

She continues to cry out in distress. "It hurts! It hurts!"

I don't know what's happening. She had no pain during the procedure. There's no external bleeding. A bad thought occurs to me the pain could mean internal bleeding. I grab more gauze and press down harder, but she pushes my hands away. The strength in her frail arms surprises me. I call for the nurse to get stat vitals and my resident.

Later, I will piece together that I must have gone through a blood vessel on insertion. While the needle was in, it tamponaded the vessel. But once I removed it, the hole in the vessel was free to bleed.

A stat ultrasound confirms a hematoma.

I'm devastated at the pain I've caused her. Thankfully, she remains hemodynamically stable. But a few hours later, I have to present the event on morning rounds. The attending responds with silence.

At the patient's door, the attending turns to me and finally speaks. "Stay out here."

My head goes hot, my heart pounds. I have to suppress a fierce desire to run away and hide somewhere. I drift over to a workstation and pretend to chart while imagining all the nurses' eyes on me.

Afterward, nobody tells me what was discussed in the patient's room, and from the furtive looks cast in my direction, I'm too afraid to ask.

My resident tells me at some point later that day that the patient doesn't want me to be a part of her care anymore. I don't know what to say, so in my post-call haze, I just nod.

She's able to discharge to home a few days later, but I have no part in her discharge.

I don't remember the rest of that rotation. I know that eventually the month ended, and I moved on to the next service. I put it behind me and buried the shame in my work.

And I never spoke of it to anyone.

I never was allowed to debrief about it. I never was given feedback on it. I was given the message that I had screwed up and I was no longer worthy of caring for the patient.

Expert shame researcher Bren Brown writes, "Shame works like the zoom lens on a camera. When we are feeling shame, the camera is zoomed in tight and all we see is our flawed selves, alone and struggling."

What it would have meant to me if the attending, or the resident, had instead had an honest conversation. Maybe shared a time they made a mistake too. Looking back now, I imagine the resident might have been concerned that he would be found out for not being in the room with me to supervise. Although even if he were, the hematoma might still have happened. Of course, I never told the attending that the resident wasn't there. The hidden curriculum had been well ingrained in me.

I know now that it's unlikely that the attending had practiced in a mistake-free vacuum. But perhaps talking about mistakes had never been modeled for him either. To talk about it might have meant confronting his own shame.

What it would have meant to me as a trainee if I could have stayed with the team on rounds that day. If the attending had explained to the patient that the superficial blood vessels in the abdominal wall become dilated in end-stage liver disease. The hematoma could have happened with anyone wielding the needle. I could have apologized and continued to be a part of her team instead of being ostracized. Because if my team had shunned me, had there been any chance of my patient not doing the same?

As Brown writes, "Shame keeps worthiness away by convincing us that owning our stories will lead to people thinking less of us. Shame is all about fear. We're afraid that people won't like us if they know the truth about who we are."

That shame has lived inside of me for 20 years. Today, I release it here by owning my own story. I hope others will join me. Let's model a better culture for our incoming interns.

Do you have a story of shame in medical training? Share it in the comments below.

Follow Medscape on Facebook, Twitter, Instagram, and YouTube

About Dr Jennifer Lycette

Visit link:
Shame in Medical Training, and Owning Our Stories - Medscape

Read More..

Thinking Differently: The Most Important Thing You Need to do to Advance Your Company – insideARM.com

Today I'm interviewing Ray Peloso, CEO of Katabat,a software company that helps clients collect more dollars and reduce charge-offs by helping them deploy collection strategies, omnichannel strategies and synchronize and orchestrate offers across the entire collection spectrum.Ray truly embodies the theme of this series because he is indeed a different thinker. Watch our interview (or read it below) about deep thinking, collaboration, and how to minimize distractions to make your team as productive as possible.

Stephanie Eidelman:

Hi, I'm Stephanie Eidelman, CEO of The iA Institute and insideARM. I'm here today with Ray Peloso, who is the CEO of Katabat. Ray was recently here with me, but now he's back for a different kind of conversation. This one is under the banner of our Innovation Council Think Differently series. And let me tell you, Ray is a different thinker. So this will be very interesting.

Ray Peloso:

Great. Well, as always, Stephanie, it's a delight to spend time with you. So hopefully we can have a bit of a controversial conversation today.

Stephanie Eidelman:

We'll do our best. So we agreed to talk about two topics that we'll weave together. The first one is, What book or of any genre really has expanded your thinking the most and how and why? The other is, Do your best ideas come from collaboration with others or deep thinking on your own, and how does this process work in your organization? I'll leave it to you to get started on your thoughts.

Ray Peloso:

Great. I think the setup is important here, which is we are a software company and for years we've had a distributed workforce. We've been able to recruit and hire people offshore as well as onshore. We've had headquarters in Delaware, but we've always over the years supplemented with hiring talented people wherever they live. All of which becomes really interesting in the post COVID world of do you bring, people back into the office, or do you allow people to live where they want to live? So it unpacks a whole bunch of interesting questions. To tie that together, as a backdrop with the book I read, it's a book called Deep Work and the author's name is Cal Newport. For any of your listeners, I'd be delighted to talk a lot about it. We read it as a management team probably two years ago and we've had controversial, but I think really productive, discussions and even practices around some of the key lessons that came out of that book. When I saw your list of topics, I thought it'd be fun to talk about.

Stephanie Eidelman:

I love that. What are some of those key lessons?

Ray Peloso:

I'm going to start with one quote and then we'll make the rest of this conversation. In the introduction, what he writes is, "In the age of network tools, knowledge workers increasingly replaced deep work with shallow work, constantly sending and receiving emails and texts like human network routers with frequent breaks for quick hits of distraction." I remember reading that thinking, wow, that sounds like how I spend a lot of my days. And I'm pretty sure it's how a lot of my team spends a lot of their days. There are a bunch of fundamental ideas here, but a core idea is that in a knowledge economy, none of us manufacture anything. I don't manufacture cars or widgets. Your brain and your individual contributions ultimately are what create value and differentiate you.

[article_ad]

Ray Peloso:

So how you think about how you manage your knowledge and tap into your talents is critical. This will weave into collaboration and I'll let you leave me with a couple of questions, but to throw out a little controversy, there has been a lot of research in the last decade or so around workplace design looking at whether collaborative open table structure is productive, not productive, more effective, less effective, etc. That's too long a topic to go through, but there is a body of thinking that Deep Work presents that says if there is a wild amount of distractions, it actually erodes the ability of the individual in a knowledge economy to be productive. I'll stop there so you can guide me from here.

Stephanie Eidelman:

I would say a number of things. First of all, I think you're right. And I have been both in those big open offices in the mid-1990s, I worked for an internet startup and we had balls and we had stuffed animals and people throwing things and yelling and having fun. And meanwhile, you had to have business development conversations on the phone in the midst of it. And it was just all part of it. And as a business owner, I have created that open space as well. And I think you're right. I have learned that you need that place to do deep work. Now in our company, what happens is you walk into a space that's open that has people there, but it's silent. Everybody has headphones on and they're doing their work. And sometimes, you know, we have collaboration, but that's why, because of this challenge you raised.

Ray Peloso:

So let me give you two thoughts and then we can unpack. First is it goes well beyond ambient noise. There's absolutely distraction of somebody walking by or talking. The book really drills into all of those IMs all day, all of those emails that happen all day...the sort of "environment of distraction." And they tell anecdotes that are always helpful in book writing. Carl Jung and great inventors by and large went off and spent time alone to allow their minds to focus on the big problems.

New Speaker:

The second point I would make is that they sort of articulate the chemical costs of your brain constantly getting distracted. In a nutshell, every time your brain is distracted, it takes a few seconds to refocus. When you do the math of how many times an hour, a day, a week, you're distracted and then how long it takes you to refocus. So the book really goes through the costs of collaboration. Because if somebody just swings by your cubicle with hey, I've got a great idea, it actually has distracted you.

Stephanie Eidelman:

Yes. It rings true for me. I'm one of these people who does get distracted by the task. I like to keep things moving. I know that if somebody asks me a question and for me, it typically happens on email, but it might be an IM as well, I want to answer it. I want to keep them moving. I'm very conscious of not stopping their progress. So whether it's me reminding them to answer their own question or me answering for them.

However I see that I advance my company most when I do that deep thinking work, those are the times that I have really pushed a ball forward. What I wonder though is that the noise people have, you mention the constant IM chatter, for instance, which definitely happens in my world. I know that my team is often chatting with each other. But you can't dictate though that they can't do that. It won't stop the mind from wanting to do that.

Ray Peloso:

Right. Gosh. So the first thing I'll tell you is that doing what we talked about is really hard. So I don't want at all to suggest that we're perfect because we struggle every day with how to take these ideas and put them into practice. I empathize with your comment which is that very often I think my best contribution to the company is keeping things moving. But I've actually learned that my personal discipline to stop trying to move things along and to actually think through what I want to move along and why can actually be quite more impactful. This leads to the classic point of one or two things done really well is probably a lot more valuable than 35 things done simultaneously and rapidly. And so we continue to try to think through those lessons.

I'll pull in one other concept to give the listeners some practical applications. There's this infamous thing called the Bezos memo.

Ray Peloso:

So Amazon (you can go Google this) around, forcing people not to use PowerPoint decks, but to actually write out their arguments in long-form memos. Part of the practice we're adopting is to take a few hours each day or one hour each day, and articulate your thoughts and organize your thoughts in written form in the form of deep work. And we have found better ideas, more well thought out, more persuasive. So there's something that Jeff Bezos and Amazon really tapped into. So we're not making up new ideas. We're sort of stealing good ideas that we're reading about elsewhere. But it ties into deep work, which is you can't write a thoughtful coherent argument if you're constantly distracted.

Stephanie Eidelman:

I think that's very true. Here's another thought that's related. Something I've noticed in our company is that when we have a management meeting and we've got five people there and somebody brings up a topic, I noticed that discussion is not necessarily as productive with five people as it is with two people. Although you think five people, five minds, you get more input, but people I think are reluctant to step on each other or say something that somebody else might think is stupid or inappropriate or whatever the barrier is. It's interesting that getting that unit down to two people -- and I see it over and over again -- and maybe even one person in certain circumstances, is even the better unit. It's probably for the same reason.

Ray Peloso:

Yeah. Two thoughts. Number one is... I think it might be Bezos or maybe Elon Musk...somebody has this pizza pie rule, which is any meeting that requires more than one pizza pie is probably too large a meeting, which is just kind of a small team rule which we find to be useful. And we use the Bezos memo. So I'll work with my chief product officer or my engineer and we'll actually have small group discussions with these -- my second point, which is having a straw man. So again, this topic sort of bumps into collaboration. And how do you collaborate? How do you make collaboration effective? There is absolutely a great role for collaboration in the workplace, but "Hey, here's an open topic, let's just go around the room for an hour and a half" is less productive in my opinion than somebody going off doing a first draft. Here's what I think we should go do and why. And then using that strawman in an iterative way, over a period of time to collaborate. That's what we try to do.

Stephanie Eidelman:

A hundred percent. That rings so true from our work in the Innovation Council. We can't possibly bring an open-ended topic to the group. There's got to be a straw man that people are asked to respond to or at a minimum, small groups are assigned specific questions to answer.

Ray Peloso:

Right. So there's a point in the book because I think this whole thing started around this book where they talk about the perfect physical architecture of the workplace. And it's a theoretical point, but it's like hub and spoke, which is Stephanie has her office because it's really important for her to have quiet deep work time, but she can leave her office and go into the common area to get a sounding board, to get a reaction, to pull someone in and say, Hey, critique my thinking, critique my work. Again, it's an academic book, but it reinforces the point that there is absolutely a critical role for collaboration. People shouldn't be working in isolation, but designing collaboration is what's important.

Stephanie Eidelman:

It'll be interesting to see how that comes about in this world where many people are working remotely; how do you design that common area? It's of course, when you say, "Okay, on Thursday we're all going to get together, or once a quarter"...Creativity and collaboration don't happen on a schedule like that. But if you did have a physical space where everybody had an office, and then you had this cool collaborative area, would people be in that collaborative area at the same time?

Ray Peloso:

Going through the logistics of it is hard. That's why these guys are college professors writing books.

Stephanie Eidelman:

And that's where the IM actually comes into play. To some degree, maybe there's a combination of calendar management and that kind of disruption or mechanism for disruption. Because if I want to ask something of someone on my team, I try to look at the calendar first and make sure that they're not on a call or in a meeting. Of course, they may be doing deep thinking at that time, in which case we'd have to have the discipline to mark that on our calendar too. Maybe there's a clue in there as to when people are interruptible and when they're not.

Ray Peloso:

It's logistics, but how each of us manages our calendar and how each of us manages our calendar with our coworkers is a huge part of all this because there's randomness and chaos throughout the day unless tribal rules are established. And we struggle with that. We want our colleagues to carve off time. One of the things we're doing very tactically, by the way, is we're creating office hours. We're basically saying the product managers are available every day from 8:30 to 9:00 to answer questions. And in exchange, we're going to ask you to leave them alone from 9 to 12 so they can work on their work. So we're trying a lot of things to figure out a way within an ecosystem of lots of moving parts and people and activity to reinforce this idea.

Stephanie Eidelman:

Have any of the things that you've tried stuck?

Ray Peloso:

Yeah. So one of the points I was going to make as we wrap all this up is that deep work is really hard. You know, you're left with your private thoughts, you're left with your own ingenuity. And it is hard to turn off all of those stimuli that now we've all become so used to and actually train the brain. So I feel like there's a lot of days where I sort of fail. I want to focus on a topic and my brain gets tired. So it's really, really interesting for anybody interested in trying it. It's actually easier to read the book. It's a lot harder than you realize to practice.

Stephanie Eidelman:

That's an excellent point to end on and give people some food for thought. We will continue because it's always wonderful to hear your thoughts.

Ray Peloso:

If any listener wants to chat about it, have them call me directly. I think it's a great topic and we really are trying all of these things to be a great company.

iA Innovation Councilis a collaborative working group of product, tech, strategy, and operations thought leaders at the forefront of analytics, communications, payments, and compliance technology. Group members meet in person (and lately, virtually) several times each year to engage in substantive dialogue and whiteboard sessions with the creative thinkers behind the latest innovations for the industry, the regulators who audit and establish guardrails for new technology, and educators, entrepreneurs and innovators from outside the industry who inspire different thinking.

2021 members include:

2nd Order Solutions

AllianceOne Receivables Management

Alorica

Arvest Bank

Attunely

BBVA

BC Services

Beyond Investments

Capital Collection Management

Cedar Financial

Citizens Bank

Collection Bureau of America

Crown Asset Management

CSS Impact

Dial Connection

ERC

Exeter Finance

Firstsource Advantage

Healthcare Revenue Recovery Group

Hunter Warfield

Imagined.Cloud

InDebted

Katabat

Livevox

MRS BPO

NCB Management Services

Neustar

Numeracle

Ontario Systems

Phillips & Cohen

PRA Group

Professional Finance Company

Radius Global Solutions

Resurgent

Revenue Group

RevSpring

Spring Oaks Capital

View post:
Thinking Differently: The Most Important Thing You Need to do to Advance Your Company - insideARM.com

Read More..

Vegan pop-up Don’t Be Chick’n launches a Bay Area food truck – The Oaklandside

Ongoing Oakland pop-up Dont Be Chickn specializes in vegan chicken feasts. Credit: Dont Be Chickn

When Nkoyo Adakama went vegan four years ago, the thing she missed most was fried chicken. The Sacramento native ate a lot of it growing up, mainly from chains like Wing Stop or Chick-Fil-A. So when dreaming up a plant-based fast-food operation that could grow and eventually be franchised, fried chicken was the obvious choice.

Adakama and her restaurant, Dont Be Chickn, arrived in Oakland in December 2020 as a pop-up, most recently serving customers at the New Parkway movie theater. This week, Adakama will announce an expansion for the business, with a food truck that will stop at Lake Merritt and other Bay Area locations starting on July 3, when it will be parked at Lake Merritt. From her new truck, Adakama will serve up completely plant-based meals, including her popular platters of fried chicken, served in a number of ways: a crispy sandwich, a Nashville spicy hot sandwich, crispy fried strips and a boneless wings platter. The chicken is made from pea protein and soy, and then is battered and deep fried.

Her cluck sauce is a secret sauce of her own invention with Cajun spices and she makes numerous other sauces, like Thai chili, honey-BBQ (made with agave so as to be vegan) mango-habanero and ranch, so one can dip their chicken in a variety of sauces, McNuggets-style. She also has a soy-based shrimp thats deep-fried and served popcorn-shrimp-style.

Sides include collard greens with vegan bacon (spicy, smoky, sweet), mac and cheese (made with Daiya vegan cheese) and potato salad. And crinkle-cut fries, lots of them. Milkshakes are also on offer, using the Berkeley-based, non-dairy and plant-based ice cream Eclipse.

I tried the popular chicken strip platter. The coating has all the nooks and crannies one expects with fried chicken, though the flavor and texture of the chicken tastes like a meat substitute. But given that the flavor of real chicken itself is quite bland and it really all depends on the preparation, this derivation of fried chicken will most likely satisfy the same craving; it could also act as a substitute for fish and chips. Where I really noticed her chefs chops were in her sauces. While some used a base of Vegenaise, she told me, she made the mango-habanero one with fresh mango; each one was unique and delicious enough that it didnt matter what I was dipping into it.

One looking to get their fried fix on will be satisfied and then some; the platters portion is more than generous. I could only eat one of the strips and half the fries in one sitting, especially with a shake (which I couldnt finish, either), especially since it comes with a soft barbecue-style roll.

Adakama said when she first turned vegan, she noticed a real lack of flavor in a lot of the food she was consuming; shes trying to make up for that with Dont Be Chickn. But health food it isnt. While many people like to think that if its plant-based, its better for you, in this case, the calorie count is equivalent to the real thing.

Its an indulgence, a treat, for sure, said Adakama. She plans to add some salads and wraps to give some lighter options.

Before opening Dont Be Chickn, Adakama, 27, was working at a Sacramento MAC makeup store, while doing modeling on the side. As a plus-size woman, her plan was to work her way up the modeling ranks, while encouraging women to feel good about their bodies, no matter their size. That goal was sidelined, she said, when she was sexually assaulted.

Adakama said that she didnt talk about the attack for two years and channeled her pain into overeating. She said that it became harder for her to feel the confidence necessary to model, and then the #MeToo movement happened.

I had been silenced for two years, she said. Noting she had always felt a deep connection to animals, she suddenly realized her feeling voiceless was akin to animals having no say in determining their fate. She saw veganism as a way to express that and work through her trauma. I went vegan overnight and never looked back, she said. I knew nothing about veganism, but I suddenly didnt have a passion for modeling anymore. I wanted to be a vegan chef.

Adakama had loved to cook since she was a child; the daughter of a white mother and a Nigerian-born father, cooking was near and dear to my heart, she said, especially since her father died when she was 12, and it was he who taught her how to cook. But she certainly didnt learn anything from him about veganism.

She started experimenting with recipes and bringing food to share with her fellow employees at the MAC store. When one of them said you should sell your food, she realized they were right, and she started a vegan meal delivery service called Compassion Meals.

Compassion Meals was healthy and satisfying, she said, but she missed the flavors she remembered from conventional meat. She started veganizing fast food-style dishes, and said that she saw a lot of vegan burgers out there or vegan ribs, and realized that not a lot are doing vegan fried chicken. Its harder to master, maybe because of the batter. Its also more time consuming and a labor of love.

Once she hit upon the fast food fried chicken concept, she then needed a name. When she came up with Dont Be Chickn, she knew that was it; it was the perfect double entendre expressing that her chicken isnt chicken, and that no one should be afraid to speak their mind.

She developed a loyal following in her hometown, but all was not well. In September 2020, she posted a video on Dont Be Chickns Instagram account, in which she said that a group of white women had made false and racist claims about her business to Sacramentos health department and Better Business Bureau in an effort to shut her down.

In the video, Adakama referred to the false claims as the dark side of veganism and said that the women created profiles where they pretended to be Black people, then posted negative reviews about her business on social media. The alleged harassment was enough to prompt her to move Dont Be Chickn from Sacramento to Oakland, she said in a follow-up post. Asked about the conflict, Adakama grew visibly emotional and declined to comment, saying that shed prefer tofocus on the future.

By the end of 2020, Dont Be Chickn had started popping up again, starting with an event at Broadways Au Lounge. Its been doing a steady business ever since, attracting repeat customers that Adakama greets by name as they pick up their orders.

That personal touch is important to her, she said, and wont go away when her food truck makes its debut next week. I feel like everyone I shared my food with in the beginning is now a vegan or at least loves vegan food, she said, and that I was able to help those people around me.

Follow Dont Be Chickn on Instagram for food truck locations as of July 3, when the truck will launch at Lake Merritt.

Continue reading here:
Vegan pop-up Don't Be Chick'n launches a Bay Area food truck - The Oaklandside

Read More..

HPE Acquires Determined AI to Accelerate Machine Learning Training – HPCwire

June 21, 2021 Hewlett Packard Enterprise today announced that it has acquired Determined AI, a San Francisco-based startup that delivers a powerful and robust software stack to train AI models faster, at any scale, using its open source machine learning (ML) platform.

HPE will combine Determined AIs unique software solution with its world-leading AI and high performance computing (HPC) offerings to enable ML engineers to easily implement and train machine learning models to provide faster and more accurate insights from their data in almost every industry.

As we enter the Age of Insight, our customers recognize the need to add machine learning to deliver better and faster answers from their data, said Justin Hotard, senior vice president and general manager, HPC and Mission Critical Solutions (MCS), HPE. AI-powered technologies will play an increasingly critical role in turning data into readily available, actionable information to fuel this new era. Determined AIs unique open source platform allows ML engineers to build models faster and deliver business value sooner without having to worry about the underlying infrastructure. I am pleased to welcome the world-class Determined AI team, who share our vision to make AI more accessible for our customers and users, into the HPE family.

Determined AI accelerates innovation with open source AI solutions to build and train models faster and easier

Building and training optimized machine learning models at scale is considered the most demanding and critical stage of ML development, and doing it well increasingly requires researchers and scientists to face many challenges frequently found in HPC. These include properly setting up and managing a highly parallel software ecosystem and infrastructure spanning specialized compute, storage, fabric and accelerators. Additionally, users need to program, schedule and train their models efficiently to maximize the utilization of the highly specialized infrastructure they have set up, creating complexity and slowing down productivity.

Determined AIs open source machine learning training platform closes this gap to help researchers and scientists to focus on innovation and accelerate their time to delivery by removing the complexity and cost associated with machine learning development. This includes making it easy to set-up, configure, manage and share workstations or AI clusters that run on-premises or in the cloud.

Determined AI also makes it easier and faster for users to train their models through a range of capabilities that significantly speed up training, which in one use case related to drug discovery, went from three days to three hours. These capabilities include accelerator scheduling, fault tolerance, high speed parallel and distributed training of models, advanced hyperparameter optimization and neural architecture search, reproducible collaboration and metrics tracking.

HPC the foundation for delivering speed-to-insight and AI at scale

AI training is continuing to fuel projects and innovation with intelligence, and to do so effectively, and at scale, will require specialized computing. According to IDC, the accelerated AI server market, which plays an integral role in providing targeted capabilities for image and data-intensive training, is expected to grow by 38% each year and reach $18B by 2024.

The massive computing power of HPC is also increasingly being used to train and optimize AI models, in addition to combining with AI to augment workloads such as modeling and simulation, which are well-established tools to speed time-to-discovery. Intersect360 Research notes that the HPC market will grow by more than 40%, reaching almost $55 billion in revenue by 2024.

To tackle the growing complexity of AI with faster time-to-market, HPE is committed to continue delivering advanced and diverse HPC solutions to train machine learning models and optimize applications for any AI need, in any environment. By combining Determined AIs open source capabilities, HPE is furthering its mission in making AI heterogeneous and empowering ML engineers to build AI models at a greater scale.

Additionally, through HPE GreenLake cloud services for High Performance Computing (HPC), HPE is making HPC and AI solutions even more accessible and affordable to the commercial market with fully managed services that can run in a customers data center, in a colocation or at the edge using the HPE GreenLake edge to cloud platform.

The Determined AI team will join HPEs High Performance Computing (HPC) & Mission Critical Solutions (MCS) business group

Determined AI was founded in 2017 by Neil Conway, Evan Sparks, and Ameet Talwalkar, and based in San Francisco. It launched its open-source platform in 2020, and as a result of its focus on model training, Determined AI has quickly emerged as a leading player in the evolving machine learning software ecosystem. Its solution has been adopted by customers across a wide range of industries, such as biopharmaceuticals, autonomous vehicles, defense contracting, and manufacturing.

About Determined AI

Determined AI is an early stage company at the forefront of machine learning technology by helping customers reap benefits of high-performance computing without the required expertise or staffing. Determined AI provides an open source machine learning solution that speeds up time-to-market by increasing developer productivity, improving resource utilization and reducing risk. The company is headquartered in San Francisco. For more information, visit: http://www.determined.ai

About Hewlett Packard Enterprise

Hewlett Packard Enterprise (NYSE: HPE) is a global edge-to-cloud company that helps organizations accelerate outcomes by unlocking value from all of their data, everywhere. Built on decades of reimagining the future and innovating to advance the way people live and work, HPE delivers unique, open and intelligent technology solutions delivered as a service spanning Compute, Storage, Software, Intelligent Edge, High Performance Computing and Mission Critical Solutions with a consistent experience across all clouds and edges, designed to help customers develop new business models, engage in new ways, and increase operational performance. For more information, visit: http://www.hpe.com

Source: HPE

View post:
HPE Acquires Determined AI to Accelerate Machine Learning Training - HPCwire

Read More..

Honeywell’s Experion Operator Advisor Incorporates Advanced Machine Learning To Measure And Improve Operator Performance – inForney.com

HOUSTON, June 21, 2021 /PRNewswire/ --Honeywell (Nasdaq: HON) announced today the addition of Operator Advisor to its Experion Highly Augmented Lookahead Operations (HALO) suite. This powerful software solution enables plant owners to objectively measure gaps and drive operator effectiveness to the next level. This market-first solution presents users including oil and gas, chemical, refining and petrochemical organizations with a consolidated scorecard of enterprise automation utilization and recommended steps to address performance-related gaps.

Honeywell's solution uses machine learning-powered analytics, a type of artificial intelligence, to gather insights from enterprise data sources such as distributed control systems and funnel those insights into dashboards. These dashboards can provide operations managers and supervisors with a clear and complete view of operator performance and improvement opportunities.

By understanding how operator actions, inactions and workload levels contribute to optimal production, organizations can develop targeted training programs, make strides toward autonomous operations and build process resilience all of which can help them better compete in the digital age.

"According to the Abnormal Situation Management Consortium, 40% to 70% of industrial accidents are linked to human error," said Pramesh Maheshwari, vice president and general manager, Lifecycle Solutions and Services, Honeywell Process Solutions. "This underscores the importance of deploying an enterprise-wide competency program that empowers organizations and workers through use of advanced technologies like machine learning to improve plant performance, uptime, reliability and safety."

As part of Honeywell's Workforce Excellence portfolio, HALO Operator Advisor is a timely response to several industry trends, including the global desire for post-COVID-19 preparedness and resilience, growing operational complexity, the aging industrial workforce and the urgent need to upskill next-generation recruits.

Honeywell data reveals the transformational impact HALO Operator Advisor can have on plant operations. Potential benefits include the reduction of 75% of incidents and human errors, leading to the recovery of $1.5 million annually per plant of production loss due to worker performance; a $2 million annual reduction in operational costs by optimizing worker productivity and training and advancing toward full autonomous plant operation; a $1.3 million annual savings in headcount through optimized production; and a $1 million savings in annual maintenance costs through improved equipment reliability.

HALO Operator Advisor will be available in October 2021. For more information, visit:https://www.honeywellprocess.comand check the HALO Operator Advisor Service Note.

About Honeywell Performance Materials and Technologies (PMT)

Honeywell PMT develops process technologies, automation solutions, advanced materials and industrial software that are transforming industries around the world. PMT's Advanced Materials businesses manufacture a wide variety of high-performance products including environmentally preferable materials used for the production of refrigerants, blowing agents, aerosols and solvents, pharmaceutical packaging, fine chemicals, additives and high strength-fiber for military, law enforcement and industrial use. Technologies developed by Honeywell UOP (www.uop.com), a leading provider in the oil and gas sector, form the foundation for most of the world's refiners, efficiently producing gasoline, diesel, jet fuel, petrochemicals and renewable fuels. Honeywell Process Solutions (www.honeywellprocess.com) is a pioneering provider of automation control, safety systems, field instrumentation, fuel delivery and burners, connected plant offerings, cybersecurity, tissue and packaging materials control systems, connected utility and metering solutions, and services for a wide range of industries.

About Honeywell

Honeywell (www.honeywell.com) is a Fortune 100 technology company that delivers industry-specific solutions that include aerospace products and services; control technologies for buildings and industry; and performance materials globally. Our technologies help aircraft, buildings, manufacturing plants, supply chains, and workers become more connected to make our world smarter, safer, and more sustainable. For more news and information on Honeywell, please visit http://www.honeywell.com/newsroom.

View original content:http://www.prnewswire.com/news-releases/honeywells-experion-operator-advisor-incorporates-advanced-machine-learning-to-measure-and-improve-operator-performance-301316115.html

SOURCE Honeywell

Link:
Honeywell's Experion Operator Advisor Incorporates Advanced Machine Learning To Measure And Improve Operator Performance - inForney.com

Read More..