COMPUTING SYSTEM BACKGROUND 1. Field The present disclosure pertains to a system for connecting first user types and second user types. Particularly although not exclusively there is a system for a ‘by consent’, evergreen marketplace that does not use resumes/curricula vitae and where people can convey more than just their skills and employment history and potentially where employers can easily and quickly search for good job candidates from both the happily employed and the unemployed. 2. Background There are significant problems with the current ways in which companies look for job candidates and job candidates attempt to get gain employment. In short, despite relatively recent online advertising of candidates and job vacancies, recruitment methods have remained relatively unchanged for decades. People looking for new jobs (or a first job) develop a resume that is often filled with white lies or exaggerations in an attempt to win the eye of the recruiter. Companies looking to fill a job post let potential candidates know through various means that a particular job is open (i.e. job posting). Job posting can be done through online websites such as Indeed or using firms that search for viable candidates (i.e. “head hunters”). This eliminates hundreds if not thousands of potentially perfect candidates who are either in employment (not actively looking) or the unemployed who did not see the advertisement. This failure of the current job market place has allowed inefficiencies and inequities to creep into the system with employees feeling trapped in their current role, often at the expense of their mental health and in some circumstances, even their physical health. For example, poor management skills, particularly at team leader and supervisor levels continue to demotivate workforces, putting unnecessary stress on employees. Whilst training can in part address this issue, personnel training is always secondary to pretty much everything and the first thing cut from budgets in tough times. The end result is pay, hours and benefits that are not aligned with modern day living, and until now there was no clear path to redress the situation. On the other side of the ledger, the employers themselves are also not happy with the status quo. It is axiomatic that skills and knowledge shortages are apparent across many industries. And unfortunately, recruitment campaigns are often suboptimum. This means that employers are often forced to compromise to fill a post. This rarely works out for either party, with both the employer and employee once again looking for alternatives. This is both a waste of resource, time and money, which ultimately detracts from the company’s day to day operations. In many companies, managers are spending a disproportionate amount of their time endlessly recruiting. What is needed is an improved marketplace for both job seekers and the employed to better themselves and their families and for employers looking to fill job openings, to find a candidate who not only has the right experience, but has the right personal traits, drive and appropriate ambition to fit with the existing workforce. SUMMARY The invention provides in several aspects a computing system according to the accompanying claims. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 shows a computer system for connecting users online; Figure 2 is a flow diagram showing instructions for connecting users online; Figure 3 is a flow diagram showing further instructions for connecting users online; Figure 4 shows a flow diagram of at least one embodiment of instructions for matching perspective employees with an employer seeking to fill a job opening; FIGURE 5 shows a more detailed decision tree flow chart of at least one embodiment of the disclosed system; FIGURE 6 is a schematic showing inputs and outputs to an artificial intelligence engine used by employees or individuals to help predict and improve their career path; Figure 7 shows a weighting of user scores in one example; Figure 8 shows weighting of user scores in another example; Figure 9 shows weighting of user scores in yet another example; Figures 10 to 14 show operation of an AI engine for identifying common data and differences amongst user profiles and tracking a career path; Figures 15 and 16 shows employee and employer profiles; and Figure 17 is a flow diagram showing diagnosis and remedies for determined physiological conditions. DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS Referring to Figure 1, there is shown a computing system 10 comprising one or more computer processors 14 for executing program instructions and for receiving inputs from users over a communications network and sending outputs to users over the communications network 11. In the illustrative example of Figure 1, there are shown a plurality of host terminals 12 operated by host personnel for controlling the system or platform and such things as responding to user queries. The host terminals comprise one or more processors for executing program instructions. The platform comprises one or more computer-readable storage media for storing user profiles associated with respective users. The host terminals each comprise a RAM 16 and a hard drive memory 18 operably connected with the RAM and processors(s), for example by a BUS. Program instruction are stored on the computer-readable storage media for execution by at least one of the processors. The host terminals may, as explained above, comprise the program instructions for executing the program instructions for operating the platform, although more preferably a server 20 is provided for communicating (receiving inputs and sending outputs from and to users) via a communications network with users, typically the internet 11. A router (not shown) distributes traffic to and from the server and the communications network. The server 20 comprises one or more processors 22 for executing program instructions for operating the platform. The program instructions may be stored transiently on a RAM 24 during operation. A hard drive memory 26 stores data and programs more permanently. Bearing in mind the quantity of data to be stored if there are many thousands or millions of users, in a preferred example the platform 10 comprises a dedicated storage facility 30. The facility may be onsite or offsite, or provided in the cloud by a third party provider. The facility may comprise program instructions for execution by one or more processors 14, 22 and preferably comprises a database for storing user profiles and associating user profiles with respective users. The server 20 and host terminals 12 are operably connected to the facility for retrieving and storing data. Users connect to the system or platform 10 using a communications enabled computing device such as a laptop (or desktop) 32, tablet 34 or smart telephone 36. Laptops typically have wireless capability (e.g. wifi®) and connect to a router 38 that directs traffic to and from the laptop over the communications network 11. Tablets and smart telephones may connect wirelessly with wifi to the communications network or communicate with the internet over a data transfer telecommunications network, such as 3G, 4G or 5G. The following discussion is intended to provide a brief, general description of a method and a possible computing environment in which the invention may be implemented. Generally, instructions comprise program modules include routines, programs, objects, components, data structures, algorithms etc. that perform particular tasks or implement particular data types. Moreover, those skilled in the art will appreciate that the invention may be practiced with a variety of computer system configurations, including personal computers, server computers, hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. The invention may also be practiced in distributed computing environments (e.g. cloud computing) where tasks are performed by remote processing devices (e.g. servers) that are linked through a communications network. In a distributed computing environment, program modules may be located on both local and remote computer storage media including memory storage devices. While the invention has been described in terms of various specific embodiments, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the claims. The executable program instructions 50 will now be explained with reference to Figure 2 and subsequent Figures. Users access the platform using a web browser or by downloading, installing and running an application for the platform. The instructions generate a register or login page prompting input of registration information or user name and password. Users are prompted to create a profile or edit an existing profile. A profile comprises characteristics of users such as biographic, career and life data. Such data may include name, age, gender, race, current salary location, benefits, profession, industry, work experience, academic education, professional qualifications, extracurricular activities, etc, together with terms specifying the parameters of employment if they are to take up a position, such as salary, benefits, role, hours of work, holiday entitlements etc. Where appropriate users may select from a dropdown list or other data input tool for such things as industry that may include for example medical, legal, construction, HR, retail, or hospitality. The dropdown list or other tool may have one or more cascading submenus for example if medical is selected the submenu may include doctor, nurse, surgeon, research scientist etc. Providing drop lists for user selection facilitates searching the platform for relevant profiles. Critically in this embodiment excluded characteristics including one or more of name, gender, race and religion are not disclosed on the platform to other users, whether potential employers or employees. Therefore a potential employee remains anonymous until they input a permission confirmation to the system in response to a system request to waive anonymity in respect of a particular expression of interest by a potential employer. The expression of interest input by a potential employer includes in principle acceptance of the employee terms of engagement. These terms include parameters of engagement that a potential employee requires and may include salary, holiday entitlement and perquisites such as health insurance, company car, share bonus scheme, working from home entitlement etc. In an alternative a user may exclude one or more of name, gender, race and religion from their completion of a profile or questionnaire. Instead the system allocates users with a key that a user uses and that the system associates the profiles with respective users. Only the system or the system database stores the key and the associated user. The executable program instructions comprise instructions 100 that are described with reference to the example shown in Figure 2. The processor(s) comprise a search engine for searching profiles for comparing the user profiles of first user types with the profiles of the second user types. At instruction step 102 the system 10 receives from users respective profile data via the communications network 11. The profile data input by a user may include data relating to the user such as biographic, career or life data. The data input by a first type of user is for establishing a connection with one or more users of a second type of user. A second user inputs profile data that may include required or preferred user data that may include biographic, career or life data. The aim is where there is a match between first user data and second user data a connection is establish between a first user and a second user. At step 106 the system stores the profile data in one or more of the computer-readable storage media 16, 18, 24, 26, 30 and associates the data with respective users, preferably in a database. In one example, users are allocated with a numeric or alphanumeric membership key when they open an account. All subsequent data input is associated with the key rather than the users’ names or contact information. Alternatively users may select user names that do not identify the users. In a further arrangement the users may use an identifier such as name or contact information, and the identifier is stored, however the identifier is never disclosed without the users permissions. Step 104 prompts users to input profile data in a predetermined format by outputting to users a questionnaire. The questionnaire is populated with answers by users by selection from drop down lists. Some answers may however require narrative textual input by users. Issuing a questionnaire in a prescribed format allows profile searching to be conducted more readily. Profiles are searched at step 108 for determining common data in the profiles of first user types and the profiles of second user types. Typically the connection between first and second users is for the paid supply of goods or services. For example an employer may seek an employee with a particular set of skills in consideration of a salary. A homeowner may seek a local carpenter skilled at installing kitchens. A business may wish to contract out coding to a software company. The system has applicability to dating systems. There are numerous possibilities. The system determines at step 110 if the common data meets a threshold value. The threshold value for example such that a percentage (at least 50%, 60% 70%, 80%, or 90%) of data is common to both first and second users. Any percentage may be selected by the host dependent on multiple factors particularly monitoring of the system in use. Alternatively the seqarch engine may search for particularly categories of data that are important and return a hit only if these categories are matcghes. At step 112 the system discloses to users of the second user type those profiles of the first user type where the common data meets the threshold value. Depending on the second users’ profiles there may be a multiplicity of first users disclosed, for example hundreds of first users. It is cumbersome and time consuming to review all of these profiles and therefore the second users may wish to refine their profiles to limit the number of profiles disclosed. For example, a second user may require a employee who has fluency in French and a qualification in accountancy, but these specified parameters return too many hits. A second user may then further specify at least 5 years post qualification experience and willingness to travel. In one arrangement at step 114 the system ranks those user profiles of the first type according to the value of common data with profiles of the second user type and discloses the profiles with their respective rankings to users of the second type. Ranking may be performed based on the percentage of common data, for example a first user having 80% common data is ranked higher than a first user having 70%. The ranked users may be displayed as a list with highest ranked user top of the list and the lowest ranked bottom of the list. Other ways of disclosing ranking will be apparent, such as by colour, typeface, numbers, or letters. At step 116 the system excludes from the profile disclosure data that identifies users of the first user type including at least the name of those users. Preferably, the disclosures exclude one or more of age, gender, race, religion and any image or video data ensuring that first users are assessed purely on other data more relevant to a role. A second user in receipt of first user profiles may select one or more first users (or none if no profiles are suitable). At step 118 the system is arranged to receive from a second user a selection. The system outputs a request to the selected users to waive anonymity for establishing contact between the selected first and the second user. By selecting a first user the second user is confirming that the first user’s specified profile conditions are acceptable in principle. For example if the first user is a job seeker and specifies a salary of £X or a holidays allowance of Y days per annum then the second user (an employer) commits to those conditions. Profiles may be added to the system or edited from time to time and therefore the system searches and compares profiles repeatedly at predetermined intervals or at other trigger events, such as when a specific number of profiles have been added or edited. In another example 130 shown in Figure 3 the system is specific to employment. The system is arranged at step 132 such that the first user type are potential employees and the second user type are potential employers. At step 134 the questionnaires output to users of both types comprise categories of profile data for the users to select from a list in respective categories, the categories including one or more of: age, race, gender, religion, industry, profession, location, willingness/requirement to travel, remuneration, perquisites, hours of work, days of work, holiday entitlement, working from home, knowledge, experience, training, qualifications, education, interests, traits, psychological profiles, desires, other work preferences/requirements and image and video data. Like the first example in Figure 2, the Figure 3 example withholds one or more and preferably all of name, race, gender, religion, image and video data when disclosing a potential employees data to potential employers until a selection of first users has been made by the second user and the selected first users have waived anonymity in respect of the second user. Anonymity is not waived by first users until the system outputs to selected first users that they have been selected by a second user who wishes to open a dialogue and interview pursuant to employment. A selection is a commitment, whether contractual or otherwise, by the second user that the first users conditions are acceptable in principle and the second user will not attempt to negotiate down such things as salary and other benefits, save for exceptional circumstances. The system is arranged at step 136 to receive from an employer user confirmation that an employee user’s profile data is acceptable, storing the confirmation associated with the employer user and the employee user and outputting the confirmation to the employee user. A second user in receipt of a first user profile may consider that first user is suitable for employment but not all the requirements of the first user can be met. For example, the second user may have a budget of £X and the first user has specified a salary higher than £X. Since it may be the case that the first user would entertain offers of £X the system aims to capture this eventuality by arranging for the second user to submit a variation request that varies the terms specified by the first user. The system is arranged at step 138 to receive from an employer user a variation request relating to an employee user’s profile data, storing the variation associated with the employer user and the employee user and outputting the variation to the employee user. Further examples of a system are described below. Disclosed herein executable instructions comprising instructions for individual character matching assessment, comprising: receiving a plurality of electronic questionnaires and fact finding on a server network device via communications network, wherein the plurality of electronic questionnaires and fact finding are designed to disclose tailored job candidate profiles with video introductions and wherein the plurality of electronic questionnaires and fact finding are completed by a plurality of members, who may or may not be seeking employment or alternative employment; posting the plurality of member profiles on an anonymous basis so that a perspective employer can view the plurality of member profiles; invoking a matching process to assess an amount of overlap between the profiles of the plurality of members and a set of requirements from the perspective employer; and creating a priority list from the assessed amount of overlap to list the most desirable members in rank order for the perspective employer. In at least an embodiment the member profile may include information on the individual’s knowledge, experience, training, education, interests, traits, psychological profiles, desires, aspirations, pay (e.g. salary and benefit expectations), a video introduction of themselves and work preferences (e.g. work from home, geographic requirements, part time or full time, and so forth) Not exhaustive. The members profile can be very comprehensive, covering all aspects ordinarily included on a resume but with considerably more detail (e.g. the member has experience of various MS Office products; the profile can convey to an interested party the level of proficiency in relation to that application, ranging from Novice, low, medium, and high, Intermediate, low, medium and high, through to Expert, low medium and high) . This member comprehensive profile obviates the need for a resume and provides a platform to keep the profile evergreen as the member’s skills continue to evolve. To assure that a member’s personal data, i.e. name, address and contact information remains confidential, employers who having identified a number of members who appear to meet their job role criteria can request a member’s consent to enter into dialogue with those members. In this request for the members consent the following information is provided: company name, a specific point of contact, the company’s website, an email, a phone number and most importantly, confirmation that the members target salary, as shown on their profile, is provisionally accepted by the enquiring employer. The member having reviewed the information provided by the employer can then choose to waive their anonymity so that the parties can obtain more information and/or arrange an interview. This safeguards members privacy at all times. With comprehensive online character profiles created, the new marketplace described herein allows employers to find key members of staff with just a few keystrokes, without the hassle of trawling through resumes/curricula vitae and having many, often pointless interviews with unsuitable candidates. This is because a keyword search will throw up a short list of both employed and unemployed members. Employed members, many of whom may be happy in their current role may not have considered moving roles, however as their profile was toggled to ‘Always Looking’, the system can include their profile in any employer search, along with the unemployed actively seeking employment. It can be the acceptance by the enquiring employer of the members salary aspirations that can likely cause consent to be provided to the enquiring employer, and thus the start of re-aligning the member’s pay with the true cost of living. In at least one embodiment, employers may leave search parameters ‘live’ within the system. In such a mode the employer is constantly looking for the right skill or experience, which could come at any time as new members join daily. With a key word search and an alert, the employer can see that either an existing member or a new member now meets their job role requirements. Perhaps an existing member who has a new skill, experience or other milestone or has recently met a new educational requirement has updated their profile, producing a match. In one embodiment, the member will be able, from within their profile account, to enter an email address of any potential employer they wish to work for. For example, the member sees an advertisement for a job that interests them. To make applying for the job frictionless, they would be able to automatically send the employer an email with their profile, formatted into a conventional resume style, including key information such as notice period required, current benefits, position held, vacation days already booked and whether their employment contract has any restrictive covenants in relation to working for a competitor. They would also have the ability to add an introduction paragraph applying for the role, as conveyed in the job advert, with or without a video introduction of themselves. If the employer has not yet joined the marketplace, the marketplace will be able to contact the unaffiliated employer and attempt to get them to join the marketplace. In one embodiment, the member, having completed their comprehensive, online profile and entered their career and lifestyle aspirations, along with salary expectations by year, retirement age etc. the system will provide a learning and experience pathway to attaining the aspirations as described, including what actions are required to attain a salary of the order specified. The system will provide automatic (and targeted) motivation and visualization of the members aspirations, continually reinforcing their beliefs, encouraging to keep them to their plan. Equally, the system will advise of any slippage in the plan and invite the member to re- input their aspirations, so they are realistic and achievable. The system will advise the member if their aspirations, based on their profile data, would most likely be unachievable. Example: 18 year Junior Administrator earning $15,000 per annum and wants to be the Chairperson of the company in 12 months on a salary of $250,000 per annum. The marketplace may make money in a multitude of different ways. Members might be asked to pay a small annual fee to participate in the marketplace. Employers might be asked to pay a larger annual fee and also fees based on success in filling job vacancies. In addition, there would be a possibility of getting revenue from advertising and affiliate relationships. Members, even those happy in their role and with their current salary, will be encouraged to keep their profiles “evergreen” on the system. Members will also be encouraged to engage voluntarily with self-development, taking part in short courses and signing up to distance learning, attending webinars, volunteering in their communities etc. with the aim of providing them with additional experience and to appreciate different perspectives and views. Responsible employers who recognise their business is nothing without its hardworking staff can, with the members consent, collaborate openly with the member using their profile as a Personal Development Plan (PDP), including agreed learning milestones linked to pay reviews. When used in an evergreen and continually updated manner the profiles can be accessed by an employee’s current employer, again by consent, to improve the value and performance of the employee and to help with retention for the employer. In short, the system allows an employer, with explicit permission by the employee, to follow the learning journey and experiences of the employee. For this reason, an evergreen profile makes sense even when an employee is happy with his current employment. This is because most employees (even happy ones) are interested in bettering their role, salary, experience, learning and/or benefits. The evergreen employee profile helps both the employee and employer to maximize the employee’s satisfaction with their career and progression. A multitude of happy employees, coupled with good man management results in a low turnover of staff which is obviously advantageous for the employer and will ultimately result in higher profits. Prospective employers can equally take advantage of the evergreen profile of a specific member, again with consent. The system can be used in the following ways • Predictive salaries years into the future • Mapping training and experience to achieve life and financial aspirations, along with timeline and action plan • Follow rising stars and plan placements as part of a longer-term strategy, including identifying and communicating training requirements • Make conditional job offers – motivating individuals to complete certain training or experience in order to gain that next step in their career progression. The system may produce a results table, tailored with suggestions and recommendations. (e.g. this employee meets your criteria except for experience in Y, we anticipate this candidate will take x weeks/months to acquire the skill set you require. We recommend offering a conditional offer contingent on the employee attaining experience in Y. The fact that ‘employees’ of a particular company may have joined and created an evergreen profile is of significant interest to stakeholders, management and HR. This is important because an employer is likely to lose a highly valued employee if they are not happy with the way they are being treated in their current role and don’t understand how they can improve their career. More over as the marketplace grows, existing members in full time employment will be approached and offered better salaries, benefits and working conditions for doing the same job as they are currently performing. This puts an emphasis on companies to create excellent working conditions, with good man management, and a pay structure that pays individuals their true worth. In certain embodiments the system can be used by people who are either too young to have started their career or are unemployed and unclear what to do next. For example, the system can show a young or unemployed person a journey of learning and experience into, or back into, a desired job role. Even at a young age, entering target salaries, retirement age, pension expectations, lifestyle aspirations, home ownership, type of car, holidays etc, the individual is provided with a learning and career path to achieve and exceed their aspirations. In some embodiments, students at high school or college (with parental consent), can be guided and focused through school, college, university, with a detailed action plan to achieve their current dreams. Figure 4 shows a flow diagram illustrating one embodiment of a system comprising executable program instructions comprising instructions 200 for individual character matching assessment. At Step 202 a member completes a questionnaire with career and personal information. At step 204 the member may anonymously post the completed questionnaire on a network device via a communications network (e.g. to a website). The electronic questionnaires are designed to give in depth information on a members various attributes and desires (e.g. knowledge, experience, training, education, interests, traits, psychological profiles, desires (e.g. salary expectations), and work preferences (e.g. work from home, geographic requirements, part time or full time, and so forth). The job profile can be quite detailed (e.g. level of Excel proficiency on a 1-9 scale) and this obviates the need for a CV/resume. In step 206 the members completed questionnaire is matched with one or more employers trying to fill job opening. In some embodiment there will be a large number of both members and potential employers. The matching process in step 206 is invoked to assess an amount of overlap between the profiles of the plural members and the employer. In some embodiments a priority list is created on the network device from the assessed amount of overlap to list the most desirable member candidates in rank order for the selected job opening. In step 208 the employer may request that the member grant consent so that the employer can contact the member to obtain more information or set up an interview. In step 210 the member may decide to grant consent, if they are in fact potentially interested in the employer and the job opening. Figure 5, shows a more detailed decision tree flow chart of at least one embodiment of the disclosed system. The diagram and flow chart are self-explanatory and therefore for brevity will not be described textually herein. As shown in Figure 6, in some embodiments a multitude of different kinds of data about an employee can be inputted into an artificial intelligence engine. The engine can use this data to output various predictions and suggested path forwards that can help both the employee (or candidate employee) and the employer themselves. In one embodiment, the electronic questionnaires are presented to a network device via a web-site on the Internet, an intranet, a LAN, etc. to both an employer’s network device and a plurality of members network devices. However, the present invention is not limited to such and embodiment and other embodiments can also be used to practice the invention. The plural network devices include but are not limited to desktop computers, laptop computers, personal digital/data assistants (PDAs), smart phones, mobile phones, non-mobile phones, interactive TV systems through set top boxes for cable television (CATV), satellite television or other television networks, Internet appliances and other types of network devices. The plural network devices communicate with a one or more information servers (i.e. network devices) using one or more wired or wireless communications protocols over a communications network. The one or more information server network devices include one or more servers hosting a web-site. The one or more information server network devices may also include file servers or other types of servers. The communications network may include, but is not limited to, the Internet, an intranet, a wired Local Area Network (LAN), a wireless LAN (WiLAN), a Wide Area Network (WAN), Public Switched Telephone Network (PSTN) and other types of communications networks providing voice, video and data communications. The communications network may include one or more gateways, routers, or bridges. As is known in the art, a gateway connects computer networks using different network protocols and/or operating at different transmission capacities. A router receives transmitted messages and forwards them to their correct destinations over the most efficient available route. A bridge is a device that connects networks using the same communications protocols so that information can be passed from one network device to another. The communications network may also include one or more additional servers or access points (AP) including wired and wireless access points (WAP). The one or more servers include web-site servers, file servers and other types of servers. The one or more information server network devices include one or more associated databases. The one or more associated databases can include plural completed questionnaires in plural digital formats, including, but not limited to, Hyper Text Markup Language (HTML), Extensible Markup Language (XML), flash media, Java and various combinations thereof. Preferred embodiments of the present invention include network devices that are compliant with all or part of standards proposed by the Institute of Electrical and Electronic Engineers (“IEEE”), International Telecommunications Union-Telecommunication Standardization Sector (“ITU”), European Telecommunications Standards Institute (ETSI), Internet Engineering Task Force (“IETF”), U.S. National Institute of Security Technology (“NIST”), American National Standard Institute (“ANSI”), Wireless Application Protocol (“WAP”) Forum, Data Over Cable Service Interface Specification (DOCSIS), Bluetooth Forum, or the ADSL Forum. However, network devices based on other standards could also be used. IEEE standards can be found on the World Wide Web at the Universal Resource Locator (“URL”) www.ieee.org. The plural network devices may include a protocol stack with multiple layers based on the Internet Protocol or Opens Systems Interconnection (OSI) reference model. The protocol stack includes, but is not limited to, Transmission Control Protocol (TCP), User Datagram Protocol (UDP), Internet Protocol (IP), Hypertext Transfer Protocol (HTTP) and other communication protocols. An operating environment for the devices may include a processing system with one or more high speed Central Processing Unit(s) (“CPU”), one or more processors and one or more memories. In accordance with the practices of persons skilled in the art of computer programming, the present invention is described below with reference to acts and symbolic representations of operations or instructions that are performed by the processing system, unless indicated otherwise. Such acts and operations or instructions are referred to as being “computer- executed,” “CPU-executed,” or “processor-executed.” It is appreciated that acts and symbolically represented operations or instructions include the manipulation of electrical signals or biological signals by the CPU or processor. An electrical system or biological system represents data bits which cause a resulting transformation or reduction of the electrical signals or biological signals, and the maintenance of data bits at memory locations in a memory system to thereby reconfigure or otherwise alter the CPU’s or processor’s operation, as well as other processing of signals. The memory locations where data bits are maintained are physical locations that have particular electrical, magnetic, optical, or organic properties corresponding to the data bits. The data bits may also be maintained on a computer readable medium including magnetic disks, optical disks, organic memory, and any other volatile (e.g., Random Access Memory (“RAM”)) or non-volatile (e.g., Read-Only Memory (“ROM”), flash memory, etc.) mass storage system readable by the CPU. The computer readable medium includes cooperating or interconnected computer readable medium, which exist exclusively on the processing system or can be distributed among multiple interconnected processing systems that may be local or remote to the processing system. In another example the executable program instructions comprise instructions to weight the importance of profile data dependent on the importance allocated to a first or second user characteristic by the other of the first or second users. For example, a characteristic may be a particular qualification that a second user requires because it is specified in an insurance policy. The qualification could be a clean driving licence, or a legal, medical or accounting qualification. The characteristic may be that a first user speaks a particular language. It could be that the first user can code software in a particular format. There are many possibilities. The system in such an embodiment is arranged to receive from users profile data together with weighting factors for respective profile data, a weighting factor being an indication of the importance of each profile datum. The weighting factors are stored with respective profile data and associated with respective users. The system applies the weighting factors to a comparison of the profile data of first users with corresponding profile data of second users so that it can determine a weighted score combining the profile data with weighting factors for disclosing to second users first user profiles according to the respective weighted scores. For example the disclosed first user profiles may be listed in order of weighted scores. The system determines the weighted score by combining each profile datum with the weighting factor for that datum and to combine the weighted profile data to determine a weighted score. For example, it may be crucial that the first user has a particular characteristic such as fluency in Mandarin and therefore that profile datum is given a high weighting factor, whereas competence in MS Office ® has low importance and therefore that profile datum is given a low weighting factor. The weighting factors selectable by users may be between 1 and 0 and weighted profile datum is determined by the product of profile datum and weighting factor. For example if the weighting factor is 1 the weighted profile datum is the same as the profile datum. If the weighting factor is 0.2 and the profile datum is 3, the weighted profile datum is 0.6 (=3x0.2). The system determines the weighted score by addition of weighted profile data for a profile. If for example the profile data is made up of 100 individual profile datum then those 100 weighted profile data are added together to generate a weighted score for the profile. Typically it is the employer user who receives the greatest advantage from a weighting system since that user is more likely to receive many first user profiles in response to a job vacancy, whereas an employee user may receive profiles from only a handful of prospective employers. In addition to a comparison of profile data the weighting ranks a user based on a comparison of data and the importance of that data. In one implementation of weighting a user may apply a weighting factor of between 1 and 0. Other possible implementations are not restricted to this range (e.g.1 to 100). A factor of 1 indicates high importance and a factor of 0 indicates low importance. In practice a factor of 0 is not used because it indicates that a user’s profile data in this respect has no importance. In the simplest example shown in Figure 7, a question has a true/false answer giving a non-weighted value of 1 or 0. If a second user allocates a weight of 1 for essential, then the first user score if the answer is true is 1 (i.e.1x1). If the weighting factor is 0.5 for medium importance the score is 0.5 (i.e.1x0.5). Each question is weighted in this way and a total or aggregate weighted score calculated. The highest weighted score is ranked highest for disclosure to the second user down to the lowest weighted score which is ranked last. Weighting therefore allows second users to view first user profiles first that are a best fit with their requirements. The system 10 comprises instructions to output to users’ devices (typically second ‘employer’ users) profile questionnaires for completion by users. The questionnaires preferably comprise lists from which preferred or essential characteristics or parameters are selected and correspond to the characteristics or parameters listed for selection by the other of the first or second users in order to facilitate matching between profiles. In addition to selection of a characteristic the system prompts users to input a weighting factor for that characteristic. This factor may be from 0 to 1 although in embodiments it is 0.1 to 1 rising from 0.1 in 0.1 increments. In embodiments a slider (or other input tool) is presented to users graphically so that users can readily slide a marker to any factor between and including 0.1 and 1. The weighted scores for all questions are added together to provide a total weighted score. The system then ranks for disclosure to users the ranked total. The list of suitable users may be disclosed with highest rank first descending to the lowest rank last. Figure 8 shows a more practical example where there are 10 questions to which a first user is to respond. The second user has applied weighting to the numbered questions: Weighting Factors (F) 1: 1, 2: 1, 3: 1, 4: 0.5, 5: 0.5, 6: 1, 7: 0.5, 8: 1, 9: 0.5, 10: 1 The first user has provided responses: Responses (R) 1: 1, 2: 1, 3: 0, 4: 1, 5, 1, 6: 0, 7: 1, 8: 0, 9: 1, 10: 1 (Total = 7) The weighted score for each question is calculated by the product RxF: Weighted Responses (RF) 1: 1 (1x1), 2: 1(1x1), 3: 0(0x1), 4: 0.5(1x0.5), 5: 0.5(1x0.5), 6: 0(0x1), 7: 0.5(1x0.5), 8: 0(0x1), 9: 0.5(1x0.5), 10: 1(1x1) (Weighted total = 5) Figure 9 shows an implementation in which there are 50 answers to be completed The weighting system is not restricted to the use in employment and can be applied usefully in other fields. Another embodiment is shown in Figures 10 to 15. In the broadest sense, this embodiment identifies trends among a multiplicity of users β for output to a user α. The analysis identifies which users β have an aspect in common with a corresponding aspect of user α and for those users β which aspects are different from the corresponding aspects of user α. As illustrated, the one or more processors of the system comprise an AI engine 300 for identifying patterns in the data 302 on the system and/or on external sources of data 304, 306. External sources may for example be free to public resources or paid for resources. The data generated by the present system is considerable and therefore trends can be identified. User profiles comprise data relating to multiple different categories A, B, C, D, E, F. The categories relate to user characteristics, particular although not exclusively first user, or employee characteristics. The categories may for example be remuneration, profession, vocation, industry, role, academic qualification, professional or vocational qualification, experience, skills, holiday entitlement, pension, entitlement to work from home, or location. The user characteristics may include current, or status quo, data describing a user in relation to each category. For example current data for a user in relation to remuneration may be a salary of £50,000. A user’s role may be project manager, Industry may be construction. For one or more categories a user may specify an objective, or aspiration. For example, a user may specify as in Figure 10 a salary aspiration D of £x to be achieved within a time frame z years. The artificial intelligence engine 300 comprises executable instructions comprising instructions to output to a first user a questionnaire for population with objectives in said categories by the first user. An example for remuneration D is shown in Figure 11. A user specifies £30,000 as their current salary. Their objective is to earn a salary of $50,000 within 5 years, £80,000 within 10 years, £110,000 within 15 years and £150,000 within 20 years. Objectives may be specified in other categories other may be for example for role. A current role may be sales assistant. An objective within 5 years may be a role of sales manager, within 10 years may be a role of regional sales manager, and within 15 years to be sales director. Objectives may be specified for any suitable category. The system receives the objectives from a user ‘α’ in the completed questionnaire. The AI engine searches other user ‘β’ profiles or external sources of equivalent data for matches between the objectives of user ‘α’ and current or requested data in a corresponding category of users ‘β’. Current data is useful because it describes another user β who has already achieved the objective. Requested data is the profile data that a user β has specified is required for an employed position if they are to take up the position. Preferably the AI engine admits the requested data for analysis only if a second user has accepted that user for connection, because in this way it is known that the requested data is viable. When the AI engine has identified a match in one category it searches the data for another user β for differences between the current status of user α and the status of users β in other categories. The engine identifies the trend of by searching for differences for many users β. The system outputs to user α a report based on the differences and changes required to user α data in other categories in order to attain the aspired objective. For example as shown in Figures 11 and 12, a user α specifies objectives in category D for remuneration. One of these objectives is £50,000 within 5 years and referenced 310 in Figure 12. The AI engine identifies the trend in other categories A, B, C, E, F… (referenced 312 in Figure 12 and shaded) for those users β who receive a remuneration of £50,000. As shown the categories 312 in which there is a trend for differences in value from users β and user α In the Figure there is a difference in industry, age, role, salary, experience, skills and categories x and y. The columns of the Figure that are left unshaded are categories of user β data that are in common with user α data or considered generally not to have a material effect on remuneration, such as hobbies. The system or user α may focus the analysis by selecting other categories where there must be a match. For example, the analysis may be restricted to users β in the same industry or are the exact target age (e.g. if user α is 31 then only users β who are 36 (31+5) are considered. The system identifies the data in common and factors which are different at step 314 and outputs to user α a report based on the analysis of trends in user data. Figure 13 shows an illustration of user α and the trend in users β. The system determines from the differences between the profiles the changes required and thereby determines at least one action system. An action system comprises one or more actions that if taken by user α would lead to a probable attainment of the desired objective. Figure 14 illustrates that the system identifies the key differences 314 between profiles and from this analysis identifies at least one and preferably a plurality of action systems, or action plans, 316 that can be followed by user α in order to attain their objective. For example an action 318 may include industry, change sector within an industry, change role (e.g. promotion), relocation, increase experience, obtain a relevant career qualification, learn a language, learn coding or macros, obtain academic qualification, etc. A plurality of action systems 320 are shown as the inner square in Figure 15 referenced OP1, OP2, OP3 and OP4. There may be any number of proposed action systems. The outer part of the square 322 is the status quo of user α and the same for all quadrants in this representation. In this example user α has selected action system OP3. The action systems may be relatively simple or relatively radical. The user makes the selection according to their own preferences. It may for example be simply to obtain a qualification or more experience, whilst remaining in the same role. More radically it may comprise relocation to another region or another country, or changing career. Whichever option is selected the system formed by the processor(s) and memory comprises a tracking arrangement. The system 10 comprises executable instructions comprising instructions to receive from user α a selection of an action system. The tracking arrangement 324 displays to user α at least the next action to be completed. The tracking arrangement monitors completion of actions for the assistance and guidance of users. Diagram 326 shows tracking of a single action A and a time frame for completion. The system prompts the user to input an action status in respect of the action A1, which may include one or more of Complete, Adjust, Continue, Reset. Completion marks the action completed. In response the system displays the next action and time frame. Adjustment provides further time for completion. Continue indicates that an action has not been completed but a user wishes to continue onto the next action. Reset resets the action time frame to start. Diagram 328 shows tracking of an objective ‘O’ (£50,000 in 5 years) comprising multiple actions A1, A2 and A3 and a time frame for completion of five years in one year increments. As several actions are required in many cases to attain an objective this provides a longer term picture for a user to focus on an objective in addition to each action. Diagram 330 shows tracking of multiple objectives O1, O2, O3 and O4. Time is shown in increments of six month and markers are shown at t= 5, 10, 15, 20 for completion of objectives O1, O2, O3 and O4. The time frame may continue to expected retirement. The example shown and described in relation to Figures 10 to 15 is suitable for use by a person who is engaged in employment, unemployed, on sabbatical, or prior to starting employment. The system may be used in other ways. In a modification, the system may be used by those who may be some time away from employment. Children at school often find it difficult to relate the abstract world of academics to real world commerce and industry. The system provides a link between the two worlds. For example, a child may have aspirations to become a doctor, lawyer, builder, games programmer etc. The system determines which academic qualifications are required for any chosen career. In particular the system may identify not only the formal qualifications required but other types of experience or skills that are advantageous to employment or university entrance. If tertiary education is required the system may identify which degree course from which university best places the child for their chosen career. Since university entrance requirements can be factored in, the system can identify the grades at GCSE and A level that are required. Such a system provides focus for children under the guidance of parents or teachers. In a continuing modification the system may partner with companies, particularly those companies who operate apprenticeship schemes or sponsorship through university, based on satisfactory grade and subjects at school or college. The action system can be configured to set in place the relevant actions required on the understanding that if those actions are completed the student will be contracted by the partnering company. This type of arrangement provides considerable motivation for students. Figure 15 shows a sample of a first user (e.g. employee) profile in which a first user has input data concerning their current and previous career and also the requested data for potential employment. ‘0’ indicates excluded data and ‘1’ indicates disclosed data. Figure 16 is a sample of a second user (e.g. employer) profile specifying what characteristics it is looking for in a potential employee. In another example described in relation to the system 400 of Figure 17, historic and aspirational first user profile inputs 402 are interrogated by an AI engine 404 for markers indicative of physiological traits that may constitute an impediment to career progression and which are typically responsive to targeted therapy. Such physiological traits 406 include for example anxiety and lack of confidence that may arise spontaneously due to personality or be caused by life events 408 such as grief or redundancy. Currently, the imposition of COVID lockdown measures has caused anxiety, agoraphobia, redundancy, and many more problems. In the example shown a history of anxiety may be detected at portion A of a time line representing historic data of a user profile or a life event may be detected at portion B. Portion C represents an objective or aspiration in the future as part of career progression. For example, a user may aspire to a managerial position and have ample capacity for such a position but acknowledges anxiety around managing other staff. In order to encourage candour when users input data it is undertaken that all such data and any conclusions that the system draws from the data are confidential to the inputting user. The system adopts a similar approach in the above example by withholding personal information when submitting first user profiles to second users. The AI engine may interrogate user profiles for objective markers indicative of physiological conditions or relative markers derived from interrogating multiple different profiles. Objective markers include user data that indicates a condition either explicitly or implicitly. An explicit marker may be a user acknowledgement of historic in a past or current role. An implicit marker may include a reluctance to engage in roles involving public speaking or chairing meetings. Relative markers may be determined by the AI engine by identifying other users with matching data in some categories but differences in other categories. A simple example is where other users β have undertaken a course or received a qualification in management and are currently in a successful management position, whereas user α aspires to such a position but is anxious about it. Completing a course that other users have attained helps a user to gain confidence in relation to management and overcome anxiety. The instructions of the system cause the AI engine to output a therapy indicator on determination of a marker. The therapy indicator comprises an indication of the physiological condition. The instructions at step 410 control the processor to select from a multiplicity of therapeutic remedies appropriate for the marker, including such things as counselling, hypnotherapy or self-help books, journals or online sources in order to provide reactive or proactive improvements. In a preferred arrangement the therapeutic remedies are mapped onto the timeline for monitoring career progress together with career orientated objectives so that a user receives positive feedback on their proactive completion of therapies at step 412 for promoting confidence, encouragement, recognition, empowerment, or reward. Alternatively, monitoring may identify at step 414 that a user is not engaging with suggested and previously agreed undertakings. The system is arranged to encourage these undertakings by communications to user for promoting engagement in therapies and the benefits to self-belief, assertiveness, motivation, anxiety, acceptance, self-esteem, confidence. While the invention has been described in terms of various specific embodiments, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the claims.