Ilya Talman, Author at Roy Talman & Associates

What Comes Next: Country-Centric AI, Company-Centric AI and Copilots

Posted on November 28, 2023

For all of the different AI models that are arriving, from Amazon to Bard to OpenAI, there is a new degree of it – the version that will be learning your preferences and direction even better.

The current foundational models appear to suggest results that are close to what you’d want, but we’re so impressed by that alone that it can come up with something so fast, there still needs to be one layer that learns about certain styles.

With many different open-source projects that people are working on, a logical question persists: How are you going to make any money at it?

That lies in the next layer of AI: Countries that feature their own cities, regions and culture built into a foundational model (i.e., Indian AI models having India-centric images, discussions about Hindu culture, etc.) or organizations that want their own AI.

The idea here is that the foundational models we are seeing right now are table stakes. They will be extremely affordable and, more or less, given away. The actual costs to users will come from everything else built around those models in a very customized way.

Talman Advantage #9: A Smoother Transition Into The New Environment

Thanks to close rapport with senior managers and relationships with clients that have lasted for many years, Roy Talman & Associates has the in-depth knowledge of a firm’s work atmosphere that few can bring to the table.

As a result, we can often provide guidance on what to expect from the culture you’re about to join, which hopefully makes your integration into that environment all the more seamless.

Make your first days in a new role better than you ever expected when you Talk To Talman First.

One of the options for building on top of an AI is a possibility that Peter Diamandis and Reid Hoffman love talking about: Copilots.

Reid Hoffman says that, within five years, there will be very few endeavors that humans will be allowed to do without a copilot.

For example, if you are a doctor, an accountant, an attorney or virtually any kind of role, you will check your vital work with your copilot. You’re going to want its opinion and these copilots will be exclusively yours. You will not be training it for anyone else.

This prediction becomes all the more fascinating when you consider how nobody can accurately predict how fast that will happen since the pace of change is already accelerating.

What we can predict is that nobody is better equipped to partner with you in your hiring process for your needs of technical talent than Roy Talman & Associates. So don’t wait for change to come. Get ahead of it now and make sure you Talk To Talman First to ensure we customize your search strategy to what’s here and what’s coming. It may just be the smartest move for recruitment you can make.

The Day That Transforms How We Measure Real Economic Growth

Posted on October 4, 2023

Those who have been following my thoughts about GDP over the years know I take issue with its shortcomings in measuring actual consumption. GDP measures primarily based on price and if prices are going down, but the quantity of what’s consumed is going up, the net result paints a far different economic picture.

Case in point: You want to buy a TV with a 75” screen. In years past, this would be no small investment. Today, you can buy a 75” TV for under $500. You can also buy a 4K video camera for under $200, which is about 10% of what it used to be not that long ago.

We’re moving beyond 1080P and 12 megapixels to purchase TVs, phones and cameras that can provide clarity in the picture beyond anything we’ve seen before, but are we paying higher and higher prices to access that level of quality?

No. We are not. We are paying less for more, which goes against the traditional measurement of GDP and poses a challenge for making financial projections. Rather than viewing this scenario as a recession and potential depression due to overproduction, we could just as easily view it as migrating into the future due to positive consumption.

It could even be a combination of both, where production is happening so fast and prices are collapsing, but consumption is also happening at a rapid pace. In which case, many of the traditional “rules” of what makes for a good or bad economy do not apply.

Talman Advantage #7: We Already Know Many People At The Top

The built-in advantage of being a more specialized recruiter for over three decades is that Roy Talman & Associates established many strong relationships with senior leaders in the C-suite and Director level. How do we truly leverage that? Prior to your interview, we can provide you terrific insight on the person’s background, the questions they’re likely to ask you and even a few clues into why prior candidates were likely rejected. A recruiter that equips you with more information in advance of the interview? That just might make all the difference – if you Talk To Talman First.

Inventor Ray Kurzweil, in his estimation of The Singularity (the technological “tipping point” in time in which machines can do what humans do faster, better and without any type of human involvement to achieve this result), thought something like what we’re describing would happen in the grand scheme of things as far as high consumption and high production.

Yet, to the extent of consumption and production that we’re seeing, thanks in large part to AI, one must wonder if the rapid emergence and adoption of AI accelerate Kurzweil’s timeline.

When investor, pioneer and Singularity University founder Peter Diamandis speaks about abundance and Kurzweil speaks about The Singularity, they look at both from a technology point of view – as in the kind of technology that’s more widely accessible. They’ll typically avoid speaking to the economics of that discussion, such as the implication on prices.

Kurzweil’s fundamental theory is the law of accelerating returns, which essentially says that the cost of computing is dropping in half at an accelerating pace. These days I would say it’s not the cost of computing that’s dropping but the cost of computational intelligence.

See, if your software is twice as efficient today as it was a year ago, even if the hardware is the same, your cost of computing is the same result. Overall, by the time you combine AI models and they interact, you’ll arrive at lower costs.

What we’re learning now is that you can have Bard, ChatGPT or Copilot writing code instead of a $150,000 programmer writing code. But wait – before you automatically believe that means layoffs, it doesn’t. In fact, it’s just the opposite.

In our next Tidbit, we’ll speak to a far more optimistic – and realistic – scenario that can play out in which the economy adjusts very fast and companies recognize that, indeed, they can have much more productive employees. We’re talking about the level of a 10X Programmer that does new, more extensive tasks. Not the ones they’ve always done faster.

When people speak about new technologies such as AI and machine learning, they focus on the models themselves. Not on the people who can be transformed in their roles for the better too. We see those possibilities as very real at Roy Talman & Associates, so you should Talk To Talman First. What we’ve recognized over the last several decades at Roy Talman is that the candidate you hire should be not only the best of the best today but also the one who can manage the changes in store for you tomorrow. We have the people, tools and testing resources to help you aim higher for the candidates you deserve – not just the ones currently available.

Machine Learning Tools Ramping Up, So Why Are Companies Lagging On Adoption?

Posted on September 8, 2023

In our previous Talman Tidbit, we spoke about an avalanche of new foundational models for machine learning and how the cost of training these models is dropping at a rate of nearly 70% per year.

With these events in mind, surely you’d think more companies would jump on the bandwagon and implement machine learning models. Yet, that’s exactly where the picture gets more complicated.

For example, there has also been a significant development with hardware: NVIDIA has produced a new chip called H100 for things like OpenAI for large language model training. H100 is about 33 times faster than A100, which is NVIDIA’s GPU that everyone lived on up to this point. H100 may be a bit more expensive than A100, but at the same time, it’s nowhere near 33 times more expensive.

As a result, companies can build and test their models much faster, creating a situation where the tools seem to be accelerating.

At the same time, in my conversations with people building technologies inside various organizations, there is still a lot of inertia:

They will say, “I asked ChatGPT to write me some code and it did it really fast!”
To which I’ll say, “Well, have you looked at Copilot (Microsoft’s AI programming tool)?”

“No, we haven’t started on that.”

So, despite many machine learning models entering the marketplace and steadily dropping the cost of computing, several people are still on the learning curve.

Talman Advantage #6: The Technical Expertise Clients Highly Respect

How many account managers within a recruiting firm have technical PhDs and MSs? Not many. Yet, you’ll find several of them at Roy Talman & Associates, which our clients in the technological space have come to highly respect over the course of 30+ years. No wonder they respond quickly in real time. And when we suggest the creation of a new position just for you, they seriously consider our suggestion at a minimum and frequently call us to discuss further.

See yourself represented from a higher place right from the very beginning. Talk To Talman first.

Lex Fridman, an AI researcher and one of my favorite interviewers, was interviewing Sam Altman, the CEO of OpenAI. Lex commented that while he spends a fair amount of time writing code, he’s had Copilot for a while. From his personal experience, Fridman described two feelings:

1) The sense of excitement that he could be so much more productive and it’s more fun to write code with the help of Copilot.

2) The sense of dread that, as time passes, what does Copilot need him for?

The other comment I found very interesting by Fridman was that it takes quite a while to get better at using Copilot, which Altman agreed with.

So, on the one hand, you have a dynamic in which machine learning tools seem to be getting better, smarter and faster literally by the week.

On the other hand, people using the tools are either too conservative or have too much inertia to use them extensively.

I must admit that I haven’t heard many stories of organizations who report switching to a machine learning tool and, in turn, watching their company’s performance and productivity change dramatically.

That said, there’s no doubt that the thirst for developing new AI models will only grow from here, creating an opportunity worth seizing for companies to invest in hiring new people and accelerating their learning curve. Especially since their competitors may say all the right things about the new frontier of machine learning but, in reality, continue to drag their feet on evolving their business.

If the new developments of machine learning models are causing greater confusion than clarity, you’re not alone. Many companies find themselves at a crossroads of how and when to commit to attracting the very best technical talent in the field.

So take the easiest first step possible: Talk To Talman First. With our extensive experience over several decades in helping companies identify high-quality talent that can evolve as rapidly as they do, a conversation today can help you arrive at a greater peace of mind and, ultimately, if it makes sense for us to go forward together, arrive at the finest candidates to choose from.

New AI Models Emerging Fast, But Who’s Driving Them?

Posted on August 21, 2023

I was listening to a podcast recently featuring the CEO of an investment management firm, who was asked about GPT3 and the groundbreaking implications for a wide range of industries from it. My ears perked up when she uttered quite the jaw-dropping food-for-thought stat: She said that if GPT3 were done in 2016, it would have cost OpenAI $800 million in computing costs. Incredibly, by the time OpenAI produced GPT3, it only cost them $4.5 million in computing costs.

But wait – there’s more. In her estimate, if GPT3 were produced today, it would only cost about $450,000 in computing costs!

What’s really going on here? Where does this enormous drop in computing costs come from? The trend is that the cost of training these AI models appears to be dropping at a rate approaching 70% per year.

That’s how we can likely expect an avalanche of new foundational models.

For example, those in the financial industry are paying close attention to BloombergGPT. This first-of-its-kind model can rapidly evaluate financial data to assess risk and economic sentiment. Amazon has unveiled its Amazon Bedrock and Amazon Titan models to build and scale generative AI applications. We’ve heard plenty about Google’s Bard model, which can now write code in as many as 20 different computer languages.

The Pitch For AI Domination

If there’s one brand to keep an eye on in this great AI race, it’s not Microsoft or OpenAI. It’s Amazon.

Why? Amazon will say, “Look. You’re already our customer. You’re already familiar with AWS. We’ve already got a platform built for you. We’re cheaper than GPT4 as a foundational model and we’re already providing a computing environment that’s much more user-friendly and easier for your IT people. What’s not to like? It’s all here.”

In the meantime, I’m finding that consumers have been adapting to ChatGPT and some have been accessing Bard, even though Google has been relatively conservative in the rolling out of Bard. OpenAI sat on GPT4 for at least six months while they were making it more reliable. And Open AI internally has been continually working on cutting the cost of training for its model.

Amid this, Emad Mostaque, founder and CEO of Stability AI, claimed that GPT4 was coming up with thousands of questions the model would be quizzed on…by another model.

So, for every answer one GPT4 had, another GPT4 tried to verify the answer. Therefore, instead of human-reinforced learning, we’re getting to the next phase of machine reference learning – start with a foundational model and then add reinforced learning by making one GPT4 check the other. Mostaque pointed to this relationship as the reason the computing cost has been rapidly collapsing.

Talman Advantage #5: A Real Partner With A Plan

When a recruiter talks to you on the phone for 20 minutes just once, there’s only so much they know about you beyond the resume. On the other hand, Roy Talman & Associates will work with you to gain a robust understanding of your skill set, goals, work style preferences and more. Then, rather than “blasting” your resume out to the hiring universe with random results, we’ll make a plan with you on what order we will present you to various firms that we feel are a best fit.

Your career deserves more than a quick chat. Partner with a recruiter who can help you feel more in control of the process – as you should be. Talk to Talman first.

Essentially, I get the distinct impression that this rush of new AI models is like a lot of race cars accelerating around a track – and while they’re accelerating, you have even more cars entering the race.

The only question is: Who’s going to drive all of them? How fast will companies jump on these rapidly moving bandwagons? In our next Talman Tidbit, we’ll begin to answer this very question. We’ll also speak to the hardware side of rapid model development, including why some companies, despite their enthusiasm for machine learning, may experience some inertia on implementation

When news stories on AI and machine learning are swirling in the media, it’s hard to know what the straight story is on how fast companies are adapting to new technologies in reality. That’s when more financial and technological leaders Talk To Talman First.

With our deep knowledge over the last several decades of the movements of companies, including how their cultures are shifting, we can speak in much greater detail to how they are (or aren’t) embracing certain advancements – no matter what the headlines say. And that’s only going to help you get more clarity on how to “hedge your bets” on the investments you make on technology and candidates

Three Hiring Scenarios To Plan For In A New Industrial Revolution

Posted on August 2, 2023

In our previous Talman Tidbit, we spoke about how the acceleration of machine learning models could lead to a new Industrial Revolution.

In conversations I’ve had with several of my colleagues, specifically about programming, we see three different scenarios that could emerge over the next three years if such a new Industrial Revolution were to occur.

Scenario A: Laying Off Lower Tiers Of Technical Talent

Currently, in a functioning software development environment, there are a number of small projects that are good training grounds for junior developers. GPT4/Copilot might take over these projects. As such, there will be drastically fewer juniors hired by these shops.

What about those junior-level programmers who are already employed? What if that group becomes more productive and elevates their skill levels? You might think this equates to greater job stability – and perhaps, in some future cases, that may be true.

However, consider this: Even if we increase productivity across the board, not every programmer will be more productive at the same level.

For instance, on a scale of 1 to 10, if a programmer has a skill level of “7” out of 10 and another programmer has a skill level of “4” out of 10, you have a multiplier effect that if people learn and the multiplier is more significant for a greater number, the “7” programmer might be multiplied by 50% but “4” might get multiplied by 30%.

Everybody gets better, but the gap between the top and second tier widens.

Consequently, in the longer term, some companies may see the “4” skill level programmer as a liability and want to begin laying off some of them. After all, the company won’t be hurt that much because its cumulative productivity is still likely to improve.

Scenario B: Tech Hoarding That Favors Machines Over Technical Talent

Companies become “hoarders” in hoarding technology. They gather more and more machine learning tools to deploy for programming,

This sets off a chain of events in which companies are laying off technical people based on what we’ve seen happen at Google, Microsoft, Amazon, Twitter, Facebook, etc. There’s not a large gap between technical talent here to consider as much as favoring machine learning applications as much as possible.

Talman Advantage #4: Better Positioning For Your Best Opportunity

The reality is that, in so many situations, that “perfect job opportunity” may not be formally listed by a company. In that instance, where some may simply fire your resume off to an HR person’s email and hope for the best, Roy Talman & Associates takes a more creative and purposeful approach.

If an opening isn’t currently available that’s an ideal match for you, we’ll discuss the kind of role with you that you would be interested in and potentially prepare and present a very specific case to that particular firm to create a unique role for you. That’s called a recruiter that goes further for you – and why you need to Talk To Talman First.

Scenario C: Overhiring, Followed By A Course Correction.

Companies with minimal backlog don’t need to do much more. After rapid-fire hiring and simultaneously overestimating the backlog, they discover that they may not need 20-30% of the people they currently have. Therefore, they simply lay off technical talent. This scenario is mostly about keeping the status quo and maintaining things the way they are,

We’re currently seeing layoffs in this scenario, where nothing changes and things get done faster. It represents a type of course correction.

Let’s face it. Some larger companies overshot their expectations and overhired based on very high projections. Even so, the largest of them had the money to overhire. How could Twitter function with 7,000 employees when they’re now functioning with less than 2,000?

The answer: They had the money coming in and the idea was to grow, grow, grow. So they took on all kinds of projects while unclear whether such projects would produce great results or not but that they might as well try it. And they didn’t have to work hard or get many wins to justify trying, with interest rates being basically zero.

Where Will We Be Three Years From Now?

People might not even try to do many projects because it would take two to three years to complete. The problem with something that takes three years? By the time year one is over, customers may not want or need it. Or it may take longer or shorter than three years, which can drastically shift planning.

So it’s tough to predict what will be useful three years from now and how to be in the correct position at the right time, working for three years to get to something that makes sense to people down the line.

We may not have a crystal ball ourselves at Roy Talman & Associates, but we do have the next best thing: Knowledge on how to keep companies prepared for the internal and external possibilities that can influence hiring the very best of the best technical talent. We’ve been excelling at that for decades.

So if you’re questioning which way the economic winds are blowing and how that might impact your hiring decisions, don’t speculate. Be confident with a plan. Talk To Talman First.

Are We At The Dawn Of The New Industrial Revolution?

Posted on July 13, 2023

Several colleagues I’ve been speaking with have suggested that recent events put us at the dawn of a new industrial revolution. And if you see the factors that contributed to The Industrial Revolution back then, it’s easy to see why they may have a real point. Let’s look at the evidence.

In the late 1920s and early 1930s, there was a crisis of overproduction. Suddenly, there was too much of, well, everything. But where did this overproduction come from?

With the benefit of hindsight, we can now say that this was the period of The Industrial Revolution in which certain technologies reached a certain level of maturity. It moved us seamlessly from a time when people walked behind a plow with an ox pulling it to a period when dramatically more powerful tractors could be purchased reasonably.

At the end of the 1920s, electric motor vehicles were in ample supply and many people understood how to use them. New factories were built to dramatically speed up production and meet demand, utilizing conveyors and other tech advancements.

Well, they did more than meet the demand. They blew right by it. It’s no wonder. In a world where there are always new things to consume, advancing technologies designed to meet that demand can exceed it, causing overproduction and oversupply of products. Reflecting this oversupply, prices begin to go down and stock markets reflect that the profitability of producing products is moving sharply down.

History May Be Repeating Itself With Machine Learning

For one, let’s talk about programming and imagine you have a team of 500 people dedicated to writing code and deploying scripts in a controlled environment. We’re far beyond the age of a programmer simply writing Java code to have a widget on the screen. Still, several machine learning models can work with any programming language and take on virtually any problem.

Let’s say that the same team of 500 people is working on various projects that should take three months, six months, a year, etc. Presumably, these numerous projects with different timelines will create a particular backlog that your people need to work through.

Talman Advantage #3: The Preparation For The Interview You Deserve

You can’t go into an interview armed with only a resume to represent you. Roy Talman & Associates gets you ready for the experience with a far more in-depth level of preparation, including an evaluation of your skills in light of what today’s marketplace demands.

Through testing on certain subjects and measuring your scores against what our clients expect, you’ll be able to head into the interview knowing so much more. You’ve come too far to settle for anything less. So make sure you Talk To Talman First.

Meanwhile, a whole new slate of projects arrives.

Suddenly, you’re caught between a rock and a hard place, weighing the cost of working on the backlogged projects and the benefit of doing so against new projects that have come along and need to be dealt with. What priority comes first?

The answer isn’t necessarily to choose between the projects but to rapidly and profoundly change how we work using models such as Microsoft Copilot.

If Microsoft Copilot is offered to a variety of users or even mandated to every user, the next thing that will happen will be that some people will start figuring out how to use it better. If those who figure out how to use such tools better become much more productive, we will have a new, different kind of problem: How can we get everybody to be much more productive?

In our next Talman Tidbit, we’ll dive deeper into three different scenarios that my colleagues and I have discussed that could occur in the next three years if we are indeed at the dawn on a new Industrial Revolution. It could have great implications for the way you hire in the years to come.

No matter what economic scenario come to fruition, you’re always going to want to make sure you Talk To Talman First. Our ability at Roy Talman & Associates over the last several decades to help top companies plan, identify and screen for the very best of the best technical talent can position you for what’s coming and in the events where the world pivots. The finest companies in the financial and technology space trust us as their partner. Maybe it’s time you learned why you should join them.

ChatGPT Brings Excitement But Thin On Safety Guarantees

Posted on May 19, 2023

In the early days of ChatGPT, many people are assuming that the answers we receive are always going to be accurate and correct. Sorry. That’s not been the case. In the same breath, there is also the assumption that ChatGPT will be used to enhance our lives rather than harm our way of life.

Can we count on that, however?

Elon Musk has stated that there isn’t any fail-safe or built-in protection for people using ChatGPT or AI in general for bad purposes – so, what happens when it gets into the wrong hands? Could we see a variety of sources intentionally feeding ChatGPT certain types of questions to gain a bundle of information that could be harmful to other people? It’s not something we want to think about, but we have to in this unregulated, rapidly advancing landscape.

One of the methods to address this potential hazard is to develop a system that quickly alerts of any activity with the intent to gain harmful information, such as trying to build a bomb. In the instance of ChatGPT, we asked, “How will you prevent people from using you to build harmful products/devices?”

If it wasn’t apparent that OpenAI knew this question was coming when they released ChatGPT, it was evident in the thorough reply we received from the tool, outlining five measures that OpenAI was taking to address this concern:

1) Ethical guidelines for using their technology, including a commitment to responsible and fair use of AI.

2) Technical controls to limit the use of models for certain types of tasks or applications. For example, an API to control ChatGPT allows developers to use the model’s capabilities while limiting the types of outputs it can generate.

3) Collaboration with stakeholders and experts from various industries to identify and address potential ethical concerns related to their technology use.

4) Transparency and communication about their research and potential uses of their technology.

5) Compliance with laws and regulations, including data protection and privacy.

While these are strong statements, they only offer so much of a deterrent. In fact, a line after these five measures particularly struck us: “It is important to note that despite these efforts, there is no guarantee that the technology will not be used for harmful purposes.”

Talman Advantage #10: Stronger Negotiating Power On Your Side

The terms of your employment aren’t to be taken lightly. With our 30+ years of industry expertise, Roy Talman & Associates has a keen eye for detail during negotiations. In fact, if the help of an attorney is required for this purpose, we can suggest one. Can any recruiter offer the same result?

Don’t wonder about the outcome. Stand with a recruiter who has the track record to negotiate firmly in your favor. Make the right call and Talk To Talman First.

Here’s what the scenario comes down to: Whenever you have a new tool with specific capabilities, if it’s truly a powerful tool, it could be used for much better or for much worse, depending on your point of view. Therefore, if you’re being threatened by any tool, you must have the means to combat it. We’ve witnessed a version of this with computer viruses. But then, what happened? We developed steps to fight viruses and hacking with avenues such as 2-factor authentication, which is much harder to break into.

Investment is the key to building more robust defense systems against those who would harm us. Suppose you spent $1 billion on developing a tool to positively impact society and someone else paid $100,000 on developing a tool to harm society. In that case, it’s unlikely that the latter tool would prevail. It can cause damage and the damage could be substantial, but victory should favor those who continue to invest in protections in mind for AI.

A tool or platform that’s so Earth-shattering can be thrilling to think about on the one hand and terrifying on the other – especially regarding how it might impact the direction of your career. With technological trends that seem to shift every time the wind blows, how can you know where to commit for what you need to know today and in the next several years? Especially since you don’t know what’s coming around the corner?

Talk To Talman First. At Roy Talman & Associates, we don’t just focus on trends but also on what the top companies in industries, such as high-frequency trading, are demanding from elite talent. And because we’ve built relationships with those companies over several decades, we have a superior sense of what they want now, in the near future and even in the long haul. So we can better prepare and test your skills to be in stronger alignment. That’s called having a game plan in unpredictable times. Talk to Roy Talman about what that strategy looks like for you today.

Guiding ChatGPT Becoming A Rare Talent All Its Own

Posted on April 27, 2023

When people start using ChatGPT, they tend to ask simple questions like they would in a Google search query.

However, we’re in a whole new ballgame. You don’t ask ChatGPT simple questions.

You need to provide it with a great deal of information that might be relevant and you need to be prepared to have follow-up questions. If you don’t like the answer, you can ask it to come up with another answer and you don’t need ChatGPT to figure out the complete answer right away but build on a series of prompts that unlock further information and insight – much like having a real “conversation” with it.

Professor Christian Terwiesch of the Wharton School took this conversation with ChatGPT even further by rephrasing some questions that caused ChatGPT to respond differently. For example, Terwiesch asked a series of research-based questions that were relatively straightforward for the tool, but there was one question that he found ChatGPT answered completely incorrect. At this point, Terwiesch rephrased the question as an expert in operations research. Bingo! ChatGPT delivered the correct answer.

This suggests that, in the right circumstances, you can ask the tool questions based on specific expertise. Simply name the level of knowledge in a particular subject. You could ask ChatGPT a question as if you were an expert in nutrition to get a specific answer on nutrition. Or as a property assessor. Or divorce lawyer.

Talman Advantage #8: True Help To Hit The Ground Running

With an offer coming, do you have a solid understanding of what you’ll be doing in the first 6 months? The first year? Having placed a variety of senior people at each client’s firm, Roy Talman & Associates can help you clarify a whole lot about the environment you’re about to join, your role and the proper expectations of your new manager.

A recruiter without the overwhelming credibility that we have may not be able to shed as much light on what’s in store for you on Day 1 and beyond. So get the insight you need and Talk To Talman First.

ChatGPT may not help you advance your deep, highly specialized knowledge, but it can provide insight into new areas you may need to become more familiar with. And if you can feed it as much of a primer of information as possible in your questions, the odds are that the answers will be more accurate and detailed.

For example: On a podcast, LinkedIn Co-Founder Reid Hoffman asked ChatGPT to describe a scenario in which the tool could help a senior salesperson improve her performance. Hoffman proceeded to have a 15-minute conversation with the tool as ChatGPT first provided the function and description of the type of salesperson it would be helping – even without getting all the details of what the salesperson would be selling. Nonetheless, ChatGPT offered helpful suggestions on how to improve customer relationships, presentations, communication and more.

Then Hoffman asked ChatGPT which of his podcast episodes were the tool’s “favorites.” ChatGPT proceeded to describe three different episodes. This time, ChatGPT failed miserably, describing people that Hoffman would have loved to interview but never actually did.

The bottom line is this: Let’s have some perspective before looking for perfection from ChatGPT or similar AI iterations.

Before this moment, what was your alternative to finding detailed answers to your questions? An expert? That’s not the easiest person to access. A Google search? Good luck, considering you’ll be sifting through hundreds or even thousands of results.

As we learn how best to guide ChatGPT, the more it should continue to astound us with some of its replies. This is the first time you have had a conversation with a machine like this.

There is a line: “If you can imagine it, you can do it.” In the case of ChatGPT, we can go a very long way when we imagine what we would like the tool to do and convey it in the most explicit terms possible.

It’s not a question of whether or not these new tools will impact the kind of talent you bring into your organization but to what degree. In other words, don’t try to formulate a hiring strategy on your own. Talk To Talman First. With four decades of highly specialized experience, Roy Talman & Associates can help you identify the standard of excellence that the “best of the best” talent needs to meet in a rapidly shifting landscape. That’s how you hire tomorrow’s leaders today.

Why Big-Time Programmers are Being Influenced by ChatGPT and More

Posted on April 13, 2023

As we’ve recently discussed, the emergence of ChatGPT, Midjourney, DALL-E and other tools is taking a variety of industries by storm. We’re going beyond Google-type queries to practically have back-and-forth dialogue with these tools to arrive at more profound results for what we seek in seconds. Nobody can predict which of these will be left standing since several more will be introduced, but we can say the usage is exploding.

The big question is: Are the most respected people within specific industries using these technologies themselves, lending further credibility to them? In the technical space, the answer is a resounding Yes.

Here’s where the use of ChatGPT gets very interesting – some of the best programmers on the planet are already finding themselves influenced by it. A programmer can start with a blank slate writing code and use ChatGPT for foundational coding.

The programmer can then layer GitHub Copilot on top of that for further complexity (Copilot is a tool from Microsoft that uses OpenAI to suggest code and entire functions in real time). How so? Amid that programmer’s coding, Copilot will recognize what that individual aims to do, even without any prompts. It may then create a message that asks, “Could you use something like this,” and then offer suggestions for the type of code you could use.

Andrej Karpathy, the Senior Director of AI at Tesla for five years, was quoted last year as saying that GitHub Copilot influences as much as 50% of his code. A year later, Microsoft CEO Satya Nadella estimates that Copilot now influences 80% of Karpathy’s code.

The fact that top programmers like Karpathy are finding Copilot so useful should put everyone else on notice that if they’re not using Copilot, they’d undoubtedly better start.

Talman Advantage #7: We Already Know Many People At The Top

A recruiter that equips you with more information in advance of the interview? That just might make all the difference – if you Talk To Talman First.

Even those who need to improve in the use of Copilot should see results equivalent to what you might expect from a mid-level programmer. However, if you’re a world-class programmer such as Andrej Karpathy, using Copilot could enable dramatic results (otherwise, why use it?). The potential of these tools in the hands of elite programmers will be tremendous.

That said, you don’t have to be the most excellent programmer alive to advance in this new era. The sooner you can get highly comfortable utilizing AI tools such as Copilot in your everyday work, the more likely you will find an increased opportunity to grow and thrive in your career.

Roy Talman & Associates can guide you on this path while shedding light on the emerging roles in the technical space to match your skillset and ambition. With decades of experience to rely on, we can tell you this: Don’t take a “wait and see” approach when it comes to embracing new technologies. Make the possibilities for your career happen when you Talk To Talman First.

Battle Between AI Platforms For Your Loyalty About To Heat Up

Posted on March 7, 2023

We’re very quickly moving in a direction where there will be a battle between AI platforms. Surely one of the key reasons OpenAI was in such a hurry to release ChatGPT recently was to gain as much global market share of users as possible. Taking any longer than a year to release ChatGPT would have threatened to take them out of contention for the earliest adopters in what could be an increasingly crowded field.

There was a rumor that the release of ChatGPT caused a “Code Red” alert at Google, but the search engine giant is readying a solid response of its own. Google will soon release BARD, a chatbot trained with human feedback and developed by its AI research lab, DeepMind. There’s little doubt that Google envisions BARD as a ChatGPT competitor, touting BARD’s ability to reduce the risk of unsafe and inappropriate answers by providing the source it is using.

Meanwhile, Amazon has told its employees to stop using ChatGPT and feeding it information. The reason? Amazon will be producing its version of a ChatGPT-like tool, so it doesn’t need to help provide information to a competing tool.

Of course, that’s to name a few. In truth, within two years, we can expect to see as many as ten different platforms competing against each other. The challenge will be that people don’t want to have to feed much information into a platform such as ChatGPT. It requires specific expertise to “train” these platforms, or you risk generating results that don’t align with your request.

Talman Advantage #9: A Smoother Transition Into The New Environment

As a result, we can often guide what to expect from the culture you’re about to join, which hopefully makes your integration into that environment all the more seamless.

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The beauty and the curse of ChatGPT and the next platforms to come is that the sky may be the limit in its capability, but the people able to direct it with great accuracy are limited. Take operating systems as an example of this dynamic. Ever wonder why there are such a limited number of operating systems? Because there are a minimal number of programmers writing code.

The New Profession Of Machine Learning Trainers

The ever-evolving AI platforms will create a new profession of people who understand how to provide highly specialized training to machine learning systems. Sam Altman, the CEO of OpenAI, has frequently spoken about companies worth $1+ trillion in revenue emerging from teams that can effectively harness the potential of AI and build new layers of development upon this early foundation. As soon as people start figuring out what it will take to build the next layer on top of AI platforms (and how many platforms can support that), they can pinpoint the type of money they need to commit to continued growth.

ChatGPT might have been the first platform out of the gate, but if we assume that there will be ten platforms or more, there’s no question that a battle for survival will occur based on which platform can attract enough investment. Is there room for many platforms to support certain verticals? Frankly, it’s hard to envision that outcome.

Altman himself has stated that the number of platforms will ultimately be limited. There may be as many as 15 to 20 “contenders”, but that number could quickly be narrowed to five platforms or less. How? In a word: Financing. A company needs billions of dollars to enter this competitive field and if it doesn’t obtain sound, consistent financial backing, there’s little point in pursuing entry.

Early in the race for platform superiority, the irony is that the winners may ultimately owe their victory not to a new platform but to their existing ecosystem. Microsoft, for example, can build ChatGPT into all of its products, making it near impossible for people to move away from that platform. Microsoft CEO Satya Nadella has stated as much. Many will wind up being on the platform without even realizing it. Since Microsoft already has such a robust ecosystem, people have already bought into it across the board. Add ChatGPT integration to the mix and Microsoft’s position just became stronger than ever.

Nadella has described multiple levels of expertise required with building platforms. One of those critical layers of expertise he highlights that Microsoft has developed is the ability to build an environment where one can train ChatGPT. In other words, it’s one thing to understand how to build a massive computing environment. Having the expertise to build systems that perform all the necessary training within that computing environment is another.

Where will such data expertise come from? Of these numerous platforms, which ones will gain legitimate support and funding? Will these coveted sources of financing be exclusive to one platform?

We can best answer these questions by citing a famous movie quote:

Fasten your seatbelts. It’s going to be a very bumpy ride.

A new breed of technical talent that understands how to train machine learning systems and work with such systems will be ideal for many companies that seek to pull ahead. Is that the kind of rare individual your competitor is already talking to? Perhaps that’s why you should Talk To Talman First.

Roy Talman & Associates can position you with a plan for bringing aboard only the best talent to help your business realize its next era of remarkable growth. For every great platform, there are several superior people. Make sure more of them are under your roof by partnering with Roy Talman today.