39 Matching Annotations
  1. Last 7 days
    1. https://web.archive.org/web/20241115135937/https://workforcefuturist.substack.com/p/ai-agents-building-your-digital-workforce

      On AI agents, and the engineering to get one going. A few things stand out at first glance: frames it as the next hype (Vgl plateau in model dev), says it's for personal tools (doesn't square w hype which vc-fuelled, personal tools not of interest to them), and mentions a few personal use cases. e.g. automation, vgl [[Open Geodag 20241107100937]] Ed Parsons of Google AI on the same topic.

  2. Nov 2024
    1. these teammates

      Like MS Teams is your teammate, like your accounting software is your teammate. Do they call their own Atlassian tools teammates too? Do these people at Atlassian get out much? Or don't they realise that the other handles in their Slack channel represent people not just other bits of software? Remote work led to dehumanizing co-workers? How else to come up with this wording? Nothing makes you sound more human like talking about 'deploying' teammates. My money is on this article was mostly generated. Reverse-Turing says it's up to them to say otherwise.

    2. There’s a lot to be said for the promise that AI agents bring to organizations.

      And as usual in these articles the truth is at the end, it's again just promises.

    3. People should always be at the center of an AI application, and agents are no different

      At the center of an AI application, like what, mechanical Turks?

    4. Don’t – remove the human aspect

      After a section celebrating examples doing just that!

    5. As various agents start to take care of routine tasks, provide real-time insights, create first drafts, and more, team members can focus on more meaningful interactions, collaboration,

      This sentence preceded by 2 examples where interactions and collaboration were delegated to bots to hand-out generated warm feelings, does not convey much positive about Atlassian. This basically says that a lot of human interaction in the or is seen as meaningless, and please go do that with a bot, not a colleague. Did their branding ai-agent write this?

    6. gents can also help build team morale by highlighting team members' contributions and encouraging colleagues to celebrate achievements through suggested notes

      Like Linked-In wants you to congratulate people on their work-anniversary?

    7. One of my favorite use cases for agents is related to team culture. Agents can be a great onboarding buddy — getting new team members up to speed by providing them with key information, resources, and introductions to team members.

      Welcome in our company, you'll meet your first human colleague after you've interacted with our onboarding-robot for a week. No thanks.

    8. inviting a new AI agent to join your team in service of your shared goa

      anthropomorphing should be in this article's don't list. 'inviting someone on your team' is a highly social thing. Bringing in a software tool is a different thing.

    9. One of our most popular agent use cases for a while was during our yearly performance reviews a few months back. People pointed an agent to our growth profiles and had it help them reframe their self-reflections to better align with career development goals and expectations. This was a simple agent to create an application that helped a wide range of Atlassians with something of high value to them.

      An AI agent to help you speak corporate better, because no one actually writes/reflects/talks that way themselves. How did the receivers of these reports perceive this change in reports? Did they think it was better Q, or did all reflections now read the same?

    10. Start by practising and experimenting with the basics, like small, repetitive tasks. This is often a great mix of value (time saved for you) and likely success (hard for the agent to screw up). For example, converting a simple list of topics into an agenda is one step of preparing for a meeting, but it's tedious and something that you can enlist an agent to do right away

      Low end tasks for agents don't really need AI do they. Vgl Ed Parsons last week wrt automation as AI focus.

    11. For instance, a 'Comms Crafter' agent is specialized in all things content, from blogs to press releases, and is designed to adhere to specific brand guidelines. A 'Decision Director' agent helps teams arrive at effective decisions faster by offering expertise on our specific decision-making framework. In fact, in less than six months, we’ve already created over 500 specialized agents internally.

      This does not fully chime with my own perception of (AI) agents. At least the titles don't. The tails of descriptions 'trained to adhere to brand guidelines' and 'expertise in internal decision-making framework' makes more sense. I suppose I also rail against this being the org's agents, and don't seem to be the team's / pro's agents. Vibes of having an automated political officer in your unit. -[ ] explore nature and examples of AI agents better for within individual pro scope #ontwikkelingspelen #netag #30mins #4hr

  3. Oct 2024
    1. Essentially anything that a remote worker can do, AI will do better

      Weird notion of remote work as only screen interaction. My team works remote, meaning they think independent from any screen tasks.

    1. https://web.archive.org/web/20241012060204/https://www.felicis.com/insight/the-agent-economy

      for the image listing various AI 'agent' services. Some seem dubious as example, and not agents but generally 'ai tools'. -[ ] maak lijst v voorbeelden uit illustratie [[241012Felicislijstaiagentscorps.png]] #15mins mbt acties/sectoren die interessant lijken. Now an agent for that task....

    2. an AI-first outsourced contact center

      so much wrong with that phrase and a tell for how these corps view this tech. let's have your customers talk to machines.

    1. imperfect tools for low-stakes tasks.

      seems that way, and to mostly remain that way. I'd be curious to incorporate agents in my tasks ([[Aazai CL]] list of such tasks)

      also burying the lede much, this is the key verdict and it's in the penultimate paragraph?

    2. For now, the concept seems to be mostly siloed in enterprise software stacks, not products for consumers.

      Real agents would start at the individual level. It all smacks so much of corps automating away their own direct interaction with customers, bc they're a pain to talk to. Blind, see gripes of existing silo customers about the impossibility getting to talk to someone

    3. a customer service agent

      almost by def asymmetric, leaving customers to talk to a blind wall.

    4. The gap between promise and reality also creates a compelling hype cycle that fuels funding

      The gap is a constant I suspect. In the tech itself, since my EE days, and in people's expectations. Vgl [[Gap tussen eigen situatie en verwachting is constant 20071121211040]]

    5. And they burn more energy than a conventional bot or voice assistant. Their need for significant computational power, especially when reasoning or interacting with multiple systems, makes them costly to run at scale.

      Also costly to run at all. If this is to increase efficiency of a corp or individual it needs to be energy efficient too. Otherwise doing it yourself is the more efficient option. AI is bound to the same laws of nature as us. [[AI heeft dezelfde natuurwetten 20190715135542]] Hiding away the inefficiency in a data center's footprint and abstracting into a service fee doesn't change that dynamic ultimately.

    6. AI agents offer a leap in potential, but for everyday tasks, they aren’t yet significantly better than bots, assistants, or scripts.

      Again it's just a promise, which seems to be the AI mantra at every step.

    7. Agents frequently run into issues with multi-step workflows or unexpected scenarios

      multi step is what they're for no? Automator can do better than agents at this time it seems.

    8. There was another, arguably more immediate problem: the demo didn’t work. The agent lacked enough information and incorrectly recorded dessert flavors, causing it to auto-populate flavors like vanilla and strawberry in a column, rather than saying it didn’t have that information.

      Exactly. All promise no delivery yet. It may work if the other side is equally automated, but if it's human or a dumb web form it won't. It also reveals on the side of the human demonstrator a big lack in reflecting on their own preferences that the AI should attach to its choices.

    9. The service is similar to a Google reservation-making bot called Duplex from 2018. But that bot could only handle the simplest scenarios — it turned out a quarter of its calls were actually made by humans.

      Vgl Phillips voice automation train tickets in 90s. 'Where do you want to go' 'It's not for me but for my mom' 'Destination not found: mom'

    10. Huet gave the agent a budget and some constraints for buying 400 chocolate-covered strawberries and asked it to place an order via a phone call to a fictitious shop.

      Note this is only 'nice' from the buyer's perspective. The 'phone call' to the shop still means having a human be subject to a computer call. It also probably means you don't care about what's being bought. No back story to e.g. a gift. Beware [[Spammy handelings asymmetrie 20201220072726]]. You automate 10 million things be sent, but need to be deleted by a human e.g.

    11. Tech companies have been trying to automate the personal assistant since at least the 1970s, and now, they promise they’re finally getting close.

      Indeed. [[AI personal assistants 20201011124147]] https://www.zylstra.org/blog/2020/10/narrow-band-digital-personal-assistants/ We should start with the personal here, wrt automation, not the AI to get to quicker results: [[small band AI personal assistant]] where the personal limits the range of possible inputs for a task and the range of acceptable outputs for a task, leaving a smaller area for an AI agent to do its thing in and thus be more effective.

    12. For individuals, AI companies are pitching a new era of productivity where routine tasks are automated, freeing up time for creative and strategic work.

      Still, how much of that is already available to automate on-device? 'routine tasks automated' is not in need of AI. What are examples?

    13. Instead of following a simple, rote set of instructions, they believe agents will be able to interact with environments, learn from feedback, and make decisions without constant human input. They could dynamically manage tasks like making purchases, booking travel, or scheduling meetings, adapting to unforeseen circumstances and interacting with systems that could include humans and other AI tools.

      Agents are prompt chains that include fetching info (params!) from elsewhere for their function. vlg [[Standard operating procedures met parameters 20200820202042]] I wonder how you generalise them, other than 'go buy/book', and when you do if they are above what on-device automation can do. In the end individuals need to be able to set the params/boundaries of any agent, make it their own agent, rather than some corps agent. What I see at consumer facing level is not aiding consumers but aiding corps reduce human interaction with consumers. Agents should increase agency, is the lithmus test.

  4. Jun 2024
    1. you're going to have like 100 million more AI research and they're going to be working at 100 times what 00:27:31 you are

      for - stats - comparison of cognitive powers - AGI AI agents vs human researcher

      stats - comparison of cognitive powers - AGI AI agents vs human researcher - 100 million AGI AI researchers - each AGI AI researcher is 100x more efficient that its equivalent human AI researcher - total productivity increase = 100 million x 100 = 10 billion human AI researchers! Wow!

    2. nobody's really pricing this in

      for - progress trap - debate - nobody is discussing the dangers of such a project!

      progress trap - debate - nobody is discussing the dangers of such a project! - Civlization's journey has to create more and more powerful tools for human beings to use - but this tool is different because it can act autonomously - It can solve problems that will dwarf our individual or even group ability to solve - Philosophically, the problem / solution paradigm becomes a central question because, - As presented in Deep Humanity praxis, - humans have never stopped producing progress traps as shadow sides of technology because - the reductionist problem solving approach always reaches conclusions based on finite amount of knowledge of the relationships of any one particular area of focus - in contrast to the infinite, fractal relationships found at every scale of nature - Supercomputing can never bridge the gap between finite and infinite - A superintelligent artifact with that autonomy of pattern recognition may recognize a pattern in which humans are not efficient and in fact, greater efficiency gains can be had by eliminating us

  5. Nov 2023
    1. that minds are constructed out of cooperating (and occasionally competing) “agents.”

      Vgl how I discussed an application this morning that deployed multiple AI agents as a interconnected network, with each its own role. [[Rolf Aldo Common Ground AI consensus]]

  6. Jun 2023
    1. Reflection enters the picture when we want to allow agents to reflect uponthemselves and their own thoughts, beliefs, and plans. Agents that have thisability we call introspective agents.
  7. Oct 2022
  8. Feb 2021
    1. move away from viewing AI systems as passive tools that can be assessed purely through their technical architecture, performance, and capabilities. They should instead be considered as active actors that change and influence their environments and the people and machines around them.

      Agents don't have free will but they are influenced by their surroundings, making it hard to predict how they will respond, especially in real-world contexts where interactions are complex and can't be controlled.

  9. Sep 2020
    1. To me, abandoning all these live upgrades to have only k8s is like someone is asking me to just get rid of all error and exceptions handling and reboot the computer each time a small thing goes wrong.

      the Function-as-a-Service offering often have multiple fine-grained updateable code modules (functions) running within the same vm, which comes pretty close to the Erlang model.

      then add service mesh, which in some cases can do automatic retry at the network layer, and you start to recoup some of the supervisor tree advantages a little more.

      really fun article though, talking about the digital matter that is code & how we handle it. great reminder that there's much to explore. and some really great works we could be looking to.

  10. Aug 2020
  11. Jun 2020
    1. Nous croyons qu’au cours des décennies à venir, à mesure que ces technologies deviendront plus sophistiquées et plus répandues, il y aura un nombre croissant de personnes qui choisiront de rechercher des activités et des partenaires sexuels entièrement auprès d’agents artificiels ou dans des environnements virtuels.

      C’est l’exposé de la position défendu par l’auteur. L'argument commence par " nous croyons" il s'agit d'un jugement personnel. Les auteurs pensent qu'avec l'évolution de la technologie de la réalité virtuelle, beaucoup de personnes vont choisir cette forme de sexualité . Cependant, aucune recherche scientifique n'est cité pour confirmer leurs affirmations.

  12. Feb 2020
    1. Robinson Crusoe’s experiences are a favourite theme with political economists

      Marx refers to the thought experiment, common in economics, which is sometimes called Robinson Crusoe economics.

      Doing "Robinson Crusoe economics" consists in imagining what can be learned, if anything, from a one agent economy that will provide insight into a real world economy with lots of agents.