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AI Sentience: How Neural Correlates Setback Consciousness Research

Digital Health: LLMs for Prompt and Quality Sleep?

AI: Sleep Computational Neuroscience, Dreams, Loneliness, and Predictive Coding

The landscape of chatbot technology has seen significant evolution. Chat-bots 5-10 years ago were simple, they used State Machines. Today, Chat-bots are Large Language Models which use AI Agents instead of traditional States. I want to propose the concept of AI routing, which promises to enhance the efficiency and effectiveness of multiple LLM agents. From Deterministic to Probabilistic Automation Pre-GPT Chatbots: State Machines Originally, chatbots were Finite Determined Automation, behaving predictably with each user interaction. These chatbots functioned as "State Machines," moving from one state to another based on predefined rules. If you ever interacted with pre-GPT chatbots, most of them were straightforward. They ask for step 1, step 2, step 3. Every state was predictable. However, this is not how we dialogue, because any dialogue quickly goes out of the scope of any state. Current Stage: Transition to Undetermined Automation New generation chat-bots are Undetermined: Each state has a probability to move to the next state. This probability is determined by the random seed of the LLM model which is used. That is why this model is a Finite Undetermined Automation. Or Even Infinite Undetermined Automation The Current Landscape of AI Interaction Deterministic Supervision and Chain-of-Interaction Chain of thought (CoT) prompting is a recent advancement in prompting methods that encourage Large Language Models (LLMs) to explain their reasoning. It leverages multiple LLM calls within an expert framework to better predict the course of the dialogue, as demonstrated in research on psychiatric behavior understanding. 1 Speaking easy, it gives more logic to the input, sharing more examples with the LLM. LLMs like examples; the same as humans. Without a doubt, it boosts the quality of the outcome. How efficient is that? Well, for some models it may triple the quality: CoT is widely used in research for Math Word Problems and other topics where logical reasoning is important. Chain-of-Interaction: LLMs for Psychiatric Behavior Understanding But CoT is not used only in Math problems. In the article, researchers have put Deterministic supervisory: based on user interaction predict the next state. , Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contexts Example: Psychiatric LLM realizes a person doesn`t want to talk about drinking, the model must recognize a new state “Change talk” and push a new talk to the dialogue. This approach was proposed in the article “ prompting” where the model predicts a chain: Chain-of-Interaction Interaction Definition Involvement Assessment Valence Analysis Long story short, instead of predicting the next state of an LLM-therapist, they do multiple calls of LLM, and they use an expert framework. This expert framework and a sequence of LLM calls give better predictions of the next state of interaction. What if LLMs Start Debating? The third example of the Chain of Thought approach is ChainLM. If there is a complex question, then you can run the game like in a GAN - one agrees, the other disagrees, and they make iterations of the reasoning. Repeat until you get a response. ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting This thing is being further trained using common sense data sets. It highlights the importance of real-world observations. Because if you do the same but for regular LLMs, it may fail in reasoning, and debates will end with a meaningless point. Optimizing With AI Routing Routing is an important step to assist existing apps in creating the optimal selection of LLMs. GPT-4 can give accurate results in various topics, but is expensive, slow, and not as efficient overall, due to high price. While some other models may be cheaper, faster, and better for specific tasks. Studies such as Routerbench have highlighted the potential for cost optimization through intelligent model selection, while Tryage introduces a real-time, intelligent routing system inspired by the human brain's architecture. ROUTERBENCH: A Benchmark for Multi-LLM Routing System Advanced Routing and Coordination Mechanisms Choosing the right model for a task presents a unique challenge since different models perform differently on various datasets. Caltech researchers have proposed the Tyage architecture, inspired by the human brain's structure. In the brain, the thalamus directs sensory inputs to specific parts of the cortex. Similarly, the Tyage system is designed to direct user prompts to the most suitable Large Language Models. This approach allows for efficient processing of information, akin to how the brain handles tasks like identifying objects, detecting motion, localizing objects, and recognizing faces by routing these tasks to specialized areas for processing. Further Ideas If you manage the coordination of AI Agents, you want to get more value for the company. You don’t want to use unsafe agents in medical care startups, and you don't want to use clickbait advertisement agents in the sales scripts because they will start promoting NSFW content. Managing AI Agents is a trade-off between short-term value and long-term value. Short-term values can be money, click-through-rate, session length Long-term values are company reputation, safety Throughout the lifetime, each chat with AI Assistant within various contexts is labeled as . Context_j In mathematical terms, the goal is to evaluate and rank each Large Language Model ( ) based on a value metric within every given context ( ). LLM_i Context_j Therefore, for each specific context ( ), the appropriate LLM_i must be chosen to ensure that the value in the subsequent context ( ) is maximized, as well as maximizing the value in the ultimate context ( ). Context_j Context_(j+1) Context_inf You had an argument, and you asked, “AI what should I do?” Let`s imagine your AI is a family coach. And it must give you a piece of advice. Visiting a strip club requires money and provides immediate stress relief, but may lead to questions from your spouse shortly afterward. Meditation costs nothing, offers immediate stress relief, and does not result in questions from your spouse. Talking with your spouse may not provide immediate stress relief, but it offers benefits far beyond those of a strip club. Returning to work generates extra income, but does not directly address the issue at hand. Even in this example, our Value is a combination of personal benefits and group benefits. And this example is radical. In real life, we have to work with epsilon function and continuous A/B tests of AI agents. These challenges are typically addressed using a multi-armed bandit approach that strikes a balance between the exploration of new strategies and the exploitation of known effective ones. Following this, existing LLMs ( ) can be enhanced through a Chain of Thoughts and recurrent LLM debates. LLM_i If you found this discussion intriguing and are curious about exploring the possibilities of AI Router further, I'd be thrilled to dive deeper into this topic with you. The engineering challenges we face in advancing AI technologies are complex, but it's precisely these challenges that fuel our progress and innovation. If you're interested in a pilot project or simply wish to exchange ideas, please don't hesitate to get in touch. Together, we have the potential to shape a brighter, more innovative future

From Chatbots to AI Routing: An Essay

In this article, I discuss the possibility of artificial parenting: an issue that is relatively new to our culture. I review this issue from the perspective of the modern neurophysiological approach. Despite the novelty and the seeming surrealism of this phenomenon, some scientists have already reviewed the social implications of AI. An example of such work is “ ”. Theories of Parenting and Their Application to Artificial Intelligence I believe that this approach to AI allows us to work with the help of neural networks instead of making them do the work for us. This can yet again revolutionize the way we interact with AI, because a symbiotic relationship that can push the development and growth of new technologies as well as society as a whole. Introduction Starting from the spring of 2023 I, like many other researchers, have been working a lot in the field of training and applying artificial intelligence. I believe everyone has felt the impact of the ChatGPT boom. Within our company, we even selected a department dedicated to creating prototypes of products that utilize different AI models for their processes. The main focus was on minimizing the cost of work while maximizing the profit. Unfortunately for us but fortunately for the rest of humanity, we came to the conclusion that making big money on generative AI is unlikely. Despite multiple tries, tweaking, and adjustments AI gave us mediocre results that never came close to the high standards we set in our work. We aim for perfection but AI creates mediocre texts or images, like AI-generated Amazon product descriptions, and the market is filled with those already. Very few companies started using ChatGPT prior to its public popularity surge, in 2022. Some even managed to make more money than OpenAi. There are several well-known cases of successful use of such as . ChatGPT Joe Popelas Based on these observations, our company decided to pivot its focus from attempts to implement AI chatbots into our apps to tuning and training AI models on personal datasets. In theory, creating datasets is a relatively simple process. However, it requires meticulous and time-consuming work. It used to be tens of thousands of underpaid employees spending days checking for snow in photos. When enough data was collected, a dataset was formed and sent to the client who used it to train their neural network to detect snow in photos. This example was relevant about a decade ago. Today the dataset forming tasks have become more complex and are often performed by qualified specialists. In some cases, it’s even impossible to teach an AI to do certain work. For instance, in , I explain why a neural network can’t be trained to perform smart contract audits. this article But let’s get back to the issue at hand. Our company selected several fields of network training. The training process, in which I participated, and the one that brought me to this article, was dedicated to a person's visual attractiveness. In other words, we taught a neural network to create images of men and women according to our attractiveness preferences. The results were never meant to be objective but lucky for us, this article is not about beauty. It’s Alive It took many tries and failures for our model to start generating images that at least remotely resembled humans. More often than not, human features were combined with inanimate objects creating a surreal and sometimes creepy image. But despite failures, we didn’t stop training the model and at some point, images became more and more realistic. I spent a lot of time experimenting with different prompts and some results came out great while others still didn’t resemble anything you could see in the world. I do remember one evening in particular when the miracle finally happened. And it wasn’t exactly the miracle I expected. “Draw me a blonde woman by the ocean” “Add a surfboard” “Make her hair longer” “Change the swimsuit color to yellow” “Add a dolphin tattoo to her shoulder blade” The tasks didn’t seem too complex but I was dealing with an AI. What takes humans seconds to understand and hours to draw works exactly the opposite way with an AI. But my model added all the changes exactly as I requested. And it did it correctly. I became happy. Really happy. Also I was very excited and more importantly, very proud. I didn’t really do much but I felt very proud still. So I decided to think about it. I wanted to analyze the origin and reasons for this feeling of accomplishment. Normally, I would be happy for my own success but in this case, I wasn’t proud of myself. I was proud of the model: the way it learned and grew to understand me. It was a bizarre feeling that forced me to dig deeper. I had to go back to my memories and find a similar experience. Which wasn’t that hard to do: a single example came to mind immediately. I was once walking with my friend and her child – Angie. Angie liked to slide from a slope but she only knew how to do it the “safe” way, as her mother taught her: backward and on her stomach. But what fun is that? I wanted to help her learn the proper, exciting way to do it. Of course, Angie was afraid at first, reluctant to even try. But by the third attempt, she started to enjoy sliding down face forward. This was new and this was fun for her. Soon after, she was sliding without my help, I was standing nearby feeling so proud of her. Exactly like I felt years later, proud of an AI model successfully drawing me an inked surfer girl. Why Educating Someone Makes Us Proud? This question was only reasonable after my surprising discovery. I hypothesized that the neurophysiological mechanism of happiness caused by successfully training a child, or a kitten for that matter, has to be similar to the one caused by AI training. Our relationships with kids and pets are well-researched and often include the most advanced methods like using functional MRI to monitor responses. But no one actually bothered to hook up a programmer to an MRI and scan their brain while they’re working on an AI. Too bad, although some research on that matter is already available. And I will try to shine the light on it a little more. Let’s start with understanding why we even experience satisfaction from the process of teaching or training. For that, we would have to seek help from two works on neuroscience: and “The Neurobiology of Parenting: A Neural Circuit Perspective” “Recent Neuroscience Advances in Human Parenting”. The neurophysiological mechanism of a parent experiencing happiness for their child’s success in training is connected to several key processes within the brain. Activation of the reward system. A child’s success activates a group of neural systems called the reward system in a parent’s brain. These systems are located in the cortico-basal ganglia-thalamo-cortical loop and they are responsible for releasing neurotransmitters such as dopamine, the very molecule that causes the feeling of satisfaction and happiness. Empathy and mirror neurons. Parents often experience empathy when their child succeeds. Mirror neurons in the brain help them to feel and understand their child’s emotions which strengthens their own emotions. Oxytocin and attachment. Oxytocin, also known as the ‘cuddle hormone’, plays an important role in strengthening the emotional attachment between a parent and a child. A child’s success can stimulate the release of oxytocin, making the connection to the child deeper and pride for them stronger. Positive reinforcement and teaching. When parents see that their efforts in teaching a child bring positive results, it stimulates the processes of positive reinforcement in their brain. This doesn’t just bring satisfaction but motivates further support and training of a child. Stress regulation and anxiolytic effect. A child’s success can also lower the stress levels and anxiety of a parent since it’s a confirmation of their efficiency as a teacher. To sum it up, the neurophysiological mechanism of parents experiencing happiness as a result of their kids’ success is connected to various neurochemical systems being activated, changes in the structure and functionality of the brain, emotional reactions, and social support. These factors work together to create a positive emotional response to a child’s success in parents. Now let’s take a look at the neurophysiological mechanism of pet owners experiencing happiness for their pets’ success or positive behavior. For that, we will cite the following works: and .
To no surprise, the process activates neurochemical and neural systems that are similar to those activated in parents or even caused by positive events. “The Complexity of the Human–Animal Bond” “The Neurobiology of Love and Pair Bonding from Human and Animal Models” To make it a little simpler, we will compare parent/child and owner/pet relationships. Similarities Activation of the reward system. In both cases, when a child or a pet demonstrates a successful result, the reward system is activated. Dopamine is released and causes the feeling of satisfaction and happiness. Oxytocin and emotional attachment. Emotional attachment, strengthened by oxytocin plays an important part in relationships with both children and pets. This hormone intensifies feelings of happiness and pride. Positive reinforcement and teaching. By acknowledging their own results in the results of a child or a pet, a human experiences satisfaction. This reinforces their desire to continue teaching. Differences The complexity of emotional response. Emotional response to a child’s success is often more complex and multilayered. It includes a feeling of pride for someone’s personality development. While with animals the feeling is usually straight-forward and focused on immediate success in behavior improvement or following commands. Empathy and mirror neurons. While mirror neurons are activated in both types of relationships, the levels of empathy and the ability to understand and predict feelings are higher in relationships with children because of the more complex social and emotional dynamics. Social and cultural impact. A child’s success has a deeper social and cultural meaning to a parent. It affects identity, heritage, and social expectations, none of which normally apply to pets. Long-term perspectives and planning. Raising a child, and teaching them to adjust to the world includes long-term planning, preparing them for the future. Naturally, that can cause the emotional reactions to become deeper. Our relationships with pets are focused on more immediate and concrete results. Despite the processes being similar, the difference lies in the nature of the relationship in question. People have complex emotional and social attachments to their children that can be enriched by cultural and social aspects. Relationships with pets, while also deep, usually are free of social expectations and cultural factors. However, the neurophysiological mechanisms include similar neuro systems and brain functions. It’s reasonable to expect that the process of teaching any object in this world if we assign to it the role of our dependant, would cause a similar neurophysiological process of achieving satisfaction and the feeling of happiness. Considering that the process would also be affected by cultural issues, demographic aspects, the psychoemotional condition of the teacher, and so on, the general effect is still the same. This is why AI is quite interesting as a subject of training and education. It doesn’t just give you results, it provides an emotional response. This last part leads us to the very idea that AI might become a potential solution to the desire for companionship or even the inability to have or raise a child. Conclusion In this article, I described a minor yet surprising discovery that demonstrates how training an AI model causes a neurophysiological response that is similar to the one caused by teaching a child or a pet. This means that AI can potentially be used as a training mechanism or a replacement for educating an actual dependant. I say potentially because before coming to any serious conclusions it’s necessary to research his discovery. However, I won’t be surprised if soon we see a reincarnation of Tamagotchi that can be trained and taught. I’ll be glad if this approach makes people’s lives more fulfilling. On the other hand, by interacting with AI, we risk pushing humanity further into the artificial universe which is already pulling us in deeper and deeper every day. Unfortunately, in this case, our neurophysiology is our own worst enemy: a human brain doesn’t see the difference between satisfaction in real and fictional worlds. If we don’t want to cause the degradation of humanity as a species, we should remain cautious when interacting with these types of developments. In my next article, I will talk about the results that surprised me and the seamy side of AI training that forces us to think about changes we need to implement into our education system to avoid distorted perceptions of reality.

Artificial Parenting: A Chance to Feel for Real

After this long digression

There is a new Correspondence in , , where the authors stated that: Nature Consciousness: unicellular organisms know the secret “All life is sentient. Both life and sentience involve self-awareness, evaluation of perceived information and mutually reactive sensory and perceptual functions. For our research into the cellular foundations of consciousness, we found it most productive to start with the simplest prokaryotic species. The data indicate that unicellular organisms are highly social, display associative learning (grasping, for example, navigational routes and simple patterns) and form stable memories. They also make decisions, evaluate events, communicate within and between colonies and, fascinatingly, show a form of altruism.” Consciousness Helps to Know The summary of these observations is that consciousness helps to know. Knowing is the purpose of consciousness, or knowing is what consciousness does. All the descriptions of sentience or consciousness are knowing outcomes. Self-awareness is a known output of being or the self. Navigation, communication, evaluations, decisions, and experiences are all known. Whatever is in a habitat that is recognized by an organism is a knowing process that could be other organisms or the components of the habitat. The construction of knowing varies across species, with humans having the most properties. Theoretically, the human mind is the collection of all the electrical and chemical impulses of nerve cells, with their features and their interactions. Consciousness is produced when impulses interact. It is the specifications of these interactions with their features that decide knowing — or consciousness. Across the brain, with nerve cells and impulses, knowing processes are ubiquitous, though those defined for consciousness are associated with the thalamocortical pathway. Conceptually, about consciousness, especially in the cerebral cortex, is a feature called drift or stairs of sets of chemical impulses, where rationing or fills occur. a significant thing Synaptic clefts are established to include vesicles and receptors. It is postulated that in sets, they represent rationing stations that distinguish a taste from a smell, or an emotion from a feeling or the degree of touch, or the functions of the cerebral cortex from the cerebellum. When a set of electrical impulses strikes at a set of chemical impulses, the sets of electrical impulses have motional dimensions that pull or push for these drifts, to appropriate knowing — and experiential outcomes. The basic interaction processes of impulses are similar, the difference with the stairs or drift defines the complex consciousness of humans, with broad divisions and sub-divisions that include intelligence, memory, creativity, language, feeling, emotion, and so forth. It is from the stairs that the sense of self also exists, for every process. Access to some of those drifts are the points of intentionality, free will, or control. During controlled processes, prioritization happens briefly, before switching to pre-prioritization and back. Prioritized interactions define attention [or answering the binding problem]. It is postulated to be a result of the most rotation of a set of chemical impulses across the mind, at any instance. There is a paper in , , where the authors in the abstract stated that: Nature Rotational dynamics reduce interference between sensory and memory representations “Cognition depends on integrating sensory percepts with the memory of recent stimuli. However, the distributed nature of neural coding can lead to interference between sensory and memory representations. Here, we show that the brain mitigates such interference by rotating sensory representations into orthogonal memory representations over time. To study how sensory inputs and memories are represented, we recorded neurons from the auditory cortex of mice as they implicitly learned sequences of sounds. We found that the neural population represented sensory inputs and the memory of recent stimuli in two orthogonal dimensions. The transformation of sensory information into a memory was facilitated by a combination of ‘stable’ neurons, which maintained their selectivity over time, and ‘switching’ neurons, which inverted their selectivity over time.” Rotations Explained This says that rotations separate sensory information and stored memories. Drifts or stairs, with their push or pull for sets of impulses — as earlier described — may sometimes appear like rotations fitting with this, but when sets of electrical impulses strike chemical impulses, there is a bit of rotation as well to determine what is prioritized. Pain [and hurt] can be theoretically explained with, say, an ‘anticlockwise’ drift or rotation, whose rationing provides the experience for the sharpness felt. What all impulses do when they interact is to drive knowing. There are features of impulses in sets that include pre-/prioritization, early-splits, sequences, principal spots, bounce points, and others. Early-split explains how it is possible to see brain activities similar to a wakeful state during sleep, with an input, but to not have a response. It means the incoming inputs were split, with some going-before but with a lower magnitude than regular, which could be because of some rotation but not comparable to when the individual is awake. Organisms without a nervous system have a form of memory that does the functions of the mind for them. They can navigate and survive using a memory form that helps them to know. AI does not have a nervous system, neither does it have cells like organisms, but it has machine memory that is dynamic enough to have outputs that compare to some of those by humans. It may since it lacks sensory grounding, but some of what becomes of senses — or knowing — that humans use to relate with whatever comes in, is something it has. not have ‘experiences’ LLMs already perform a vast aspect of knowing, making their functions vital to human consciousness. They may be seen as a tool to extend human consciousness, but humans may also present for them a completion of their lack of subjective experiences or other aspects of knowing. Feature image source

LLMs | Sentience: What Does Consciousness Do and How?

This quick round-up of sales tips will help you become a top-notch seller from your first days at the office. Today salespeople have an outstanding choise of tools, services and blogs that help them sell more. However, even with all those amazing assistants, online sales continue to be stressful and complicated.  In this article, we gathered seven tips that will help you build an outstanding career in sales. 1. Find the right recipient for your message Before getting down to direct sales, you should put together a list of your potential customers. If you sell  a B2B product, start by gathering names of potential customers. After, find the contacts of the right people from their teams to contact. Many newbies repeat the same mistake: they write to the only email address related to a company they could find on the Internet. As a result, their sales pitches end up in spam and trash folders. In fact, the people who receive it can’t even understand why it is sent to a Product Manager, HR Representative, or even the CEO of the company. Tip: Salespeople often believe they can receive a reply from . Let this hint save time for you: the chance that you get a response from info@email.com is very close to zero. info@email.com What should you do in this case? First, define the job title of a person who may be responsible for the implementation or purchasing of what you’re offering. Is that a PR Specialist or maybe Head of Sales? Excellent! Now you know whom to chase. Second, search for their emails. Extensions like or will help you discover the right email through the website of the company and save your time. You can also use websites similar to , which stores thousands of contacts that belong to the AdTech industry. Once you’ve found the right person to email, don’t limit yourself to Gmail only. LinkedIn has proved to be a good tool for business negotiations as well. Email Extractor Hunter Thalamus 2. Write a perfect sales pitch The ‘elevator speech’ tactics work for online communication as well. The only difference is that in the case of emails, three minutes in the elevator turns into three seconds of reading the subject line of the email.  You can easily find lots of valuable content that can teach you , or . How to Give a Killer Sales Pitch 5 Sales Pitch Examples Too Good to Ignore 7 Successful Sales Pitch Examples and Why They Work However, having first-class writing skills doesn’t guarantee feedback from your recipient. In 2018, the across all industries was 24.8%. These seven simple rules will help you increase both the open rates and response rates: average open rate Include the recipient's name into the subject of your email.Keep the subject of your email short ( is optimal), clear, and catchy.Use simple language and bullet points to show the real value of your product for this specific customer.Don’t oversell. Don’t make your emails wordy.Follow email etiquette. Avoid overusing exclamation points and upper cases.End your email with a question that you recipient can’t answer with a short ‘yes’ or ‘no’.Don’t hesitate to set up video calls. It's a better way to build trust if you can see the person with whom you are contacting, right? 6-10 words And last but not least: follow-ups are great unless they turn into spamming with 2-3 emails per day. When sending your emails too often, you run the risk of finding yourself in the spam folder. So let’s stay sane. 3. Track and optimize your sales progress with CRM software is the No.1 tool for any seller. When you start your career in sales, make sure that you choose the right one for your work. And if you’re still a big fan of standard spreadsheets, let us explain why you won’t be able to succeed in sales without a CRM. Every day CRMs helps sellers to: Customer Relationship Management (CRM) Store all the contacts and leads in one placeTrack and access every moment of interaction with customersPay attention to every customer’s requestPreserve potential leadsClose deals right in the inboxSchedule follow-ups, bulk email campaigns, newsletters, etc.Synchronize the sales funnel with CRM stages, statuses, and tagsIdentify the weak points of sales strategyFocus on customers instead of recollecting information about themMonitor personal sales progress and much more According to , CRM software may increase the company’s sales by up to 29%. And if you’re not ready to pay for additional services, you may start with CRMs that are free to use. For example, stays free forever for sales teams of up to 2 people. Salesforce NetHunt If your company has already integrated CRM software, spend your time to explore everything that it has to offer for making your work as effective as possible. 4. Show the immediate value Your customers don’t want to know that you work in the best company in the universe, or that you sell an outstanding product that changes lives. What they do want to know is what specific problems your product can solve. Instead of focusing on the exceptional uniqueness of your product, highlight 3-5 concrete jobs that your product helps with. For example, if you’re selling CRM software you should say that it helps to: Track every step of communication with customers Remind about follow-ups Schedule and automate bulk emails Protect emails from spam filters Synchronize Gmail inbox with clients database and more. Before reaching out to your recipients, explore what exactly they are doing in the company. Read more about the company itself. This information helps you better customize your request, make it less general and more specific. Show what your product can do for your potential customers here and now. 5. Test email templates and measure results Even if you’re sure that your emails can sell anything to anyone, there’s a strong chance this isn’t the case. The reason people don’t sign up for a trial period could be that your message was unclear. This is why a “good seller” test-drives different email templates and checks stats. Which email had the highest open rate? How many website visits happened after a mass mailing? CRMs and will help you track and control all the essential numbers on your emails. email tracking software If you received no responses after your recent mailout, maybe it’s time to rewrite the letter. But before writing one, check out these with 60% or higher open rates. In fact, if you achieved an open rate of , then you can be sure that you’re doing great! 10 examples of templates 25% or higher You should also be aware of spam filters. Prior to sending your emails, . To ensure higher credibility, equip your email with a proper signature that contains your photo, job title, the company’s logo, links to your Linkedin profile, Skype or other messengers you may use for work. test them for spamminess The email should also have a proper sender’s name and never be sent from . noname@product.com 6. Be a friend Do you know the main point of the sales process? Actually, it’s not sales. The sales process is all about relationships and communication with people. There's another human being sitting on the opposite side of the monitor and reading your email. They may have a headache, overdue loan or even a broken heart at the moment of hearing from you. If you notice something like this, try not to rush the process. Show your support and compassion. Listen to your client and try to be a little bit more than a business partner. It’s a long-term strategy, but it also drives real results. By the way, your CRM also can store clients' birthday dates, names of their pets, and the sports teams they support. Keep collecting facts. You never know which information can suddenly help you close the deal. 7. Never give up While exciting and profitable, sales job can also be tough and stressful. It’s frustrating when you don’t see immediate results of your work. This is why you should never lose your heart. Hard work always pays off, remember? Be persistent and hard-working, don’t take “no” as an answer, and good luck with your sales. Originally posted at learn.g2.com

7 Most Important Tips for New Sellers

Technologies and Startups that Hack Brain

**SINGAPORE, Singapore, February 14th, 2024/FinanceWire/--**FBS, a leading global broker, celebrates 15 years since the first trader registration. To honor the significant milestone and express gratitude to its traders, the global broker is thrilled to launch the with fifteen iPhones 15 Pro Max as the tempting prizes. FBS 15 Anniversary Raffle “Established in 2009, FBS has grown into a licensed financial service provider trusted by millions of traders worldwide. We aim to reinforce our clients' confidence in trading and consistently deliver reliable financial services,” said Alexandra Zaitseva, Head of Public Relations and Events at FBS. FBS is renowned for its transparent and smooth gateway to financial markets. With over 550 trading instruments, fast and accurate order execution, over 200 payment methods for deposits and withdrawals, and 24/7 multilingual client support, FBS is always at traders’ service. The brand additionally caters to its clients, offering them varying resources for trading education and financial analytics. For instance, FBS’s market insights via live streams, webinars, e-shots, and social media have recently helped its clients collectively get over $1,000,000 on CFD gold trading in less than a week. Alexandra goes on saying, “Not only do we offer top trading conditions, but also strive to constantly enhance our services. Most recently, FBS has introduced major updates to the client verification process. The implemented face scanning or liveness check technology has reduced the average verification time by 40%. Our clients now get a more efficient venue for the vast array of financial services offered by FBS.” As of the end of 2023, FBS boasts over 27,000,000 traders worldwide and has a record IB Partners team exceeding 680,000 members. The annual trading volume of FBS's clients surpassed $543 billion by the end of the year. To celebrate its 15th anniversary, FBS runs a two-week Instagram contest, starting on February 14, 2024. Participants are invited to create a post sharing their trading journey with FBS and using #HappyBirthdayFBS hashtag. Those who want to compete for an iPhone 15 Pro Max must onboard before 04:59 (GMT+2), February 28, 2024. On February 29, 2024, fifteen iPhones 15 Pro Max will be raffled among the participants during a with Andreas Thalassinos, a veteran FX educator. special birthday stream Contact Press Office FBS press@fbs.com This story was distributed as a release by Financewire under HackerNoon’s Business Blogging Program. Learn more about the program . here

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