AI News Archive: August 12, 2026 — Part 9
Sourced from 500+ daily AI sources, scored by relevance.
- How to Create Production-Ready Code with Claude Code
Coding agents can quickly generate a lot of code. Using the likes of Cursor or Claude Code, you’re able to rapidly develop powerful and… Continue reading on Towards AI »
- Apexon targets stalled AI pilots with three AgentRise additions
Santa Clara-based technology services firm Apexon Inc. today expanded AgentRise, its agentic artificial intelligence platform, with three new components. The additions are named AgentRise Polaris, AgentRise Lodestone and AgentRise Harness. Each maps to one of three disciplines Apexon has built its client work around, called Domain & Strategy, Cognitive Architecture and Harness Engineering. Polaris covers […] The post Apexon targets stalled AI pilots with three AgentRise additions appeared first on SiliconANGLE .
Score: 32🌐 MovesAug 12, 2026https://siliconangle.com/2026/08/12/apexon-targets-stalled-ai-pilots-three-agentrise-additions/ - Techie Tonic: Why is an AI Gym Booking Agent sparking chaos in Australia?
Techie Tonic: Why is an AI Gym Booking Agent sparking chaos in Australia? Gulf News
- Norwegian startup Visoid raises $2.5 million to scale its AI-native architecture platform - ArcticStartup
Norwegian startup Visoid raises $2.5 million to scale its AI-native architecture platform - ArcticStartup ArcticStartup
- Daily.co voice agent with AssemblyAI Universal-3 Pro Streaming
Deploying Daily.co voice agents using AssemblyAI Universal-3 Pro Streaming.
Score: 32🌐 MovesAug 12, 2026https://assemblyai.com/blog/daily-co-voice-agent-with-assemblyai-universal-3-pro-streaming - When AI enters the physical world, safety gets real
When AI enters the physical world, safety gets real EurekAlert!
- AI gives tomorrow's wireless networks a clearer voice
Anyone who has struggled through a poor phone call knows the frustration of missing half a conversation. Now researchers at Queen Mary University of London, led by Paul Anthony Haigh, have developed an artificial intelligence system designed to solve an equivalent problem in high-speed optical communications.
Score: 32🌐 MovesAug 12, 2026https://techxplore.com/news/2026-08-ai-tomorrow-wireless-networks-clearer.html - Younger, wealthier households are pulling ahead on AI's benefits
Who's using AI at home and how do they use it? And is it making them more efficient?
Score: 32🌐 MovesAug 12, 2026https://techxplore.com/news/2026-08-younger-wealthier-households-ai-benefits.html - The AI Sales Engineer Is Moving Into the Meeting
As voice agents and photorealistic avatars move into enterprise software, the sales call is becoming a test case for whether AI can do more than summarize a conversation after it ends. The pressure point is familiar to anyone who has sat through a software demo: a buyer asks about a security review, integration edge case, […]
Score: 32🌐 MovesAug 12, 2026https://www.digitaltrends.com/brc/the-ai-sales-engineer-is-moving-into-the-meeting/ - The Verification Gap Behind Every AI-Generated Release
The Verification Gap Behind Every AI-Generated Release DevOps.com
Score: 32🌐 MovesAug 12, 2026https://devops.com/the-verification-gap-behind-every-ai-generated-release/ - Enterprise AI in Focus: Singapore’s AICC Says Its Routing Solution Slashes 47% of API Costs
Enterprise AI in Focus: Singapore’s AICC Says Its Routing Solution Slashes 47% of API Costs apac.entrepreneur.com
- Guest commentary: Who’s liable when AI is behind the wheel?
Guest commentary: Who’s liable when AI is behind the wheel? Automotive News
Score: 32🌐 MovesAug 12, 2026https://www.autonews.com/opinion/guest-commentary/an-guest-commentary-av-liability-insurance-0812/ - Making modernization faster, smarter and more economical in the agentic AI age
Making modernization faster, smarter and more economical in the agentic AI age IT Pro
- TrustKernel Launches PlugClaw, a Thumb-Sized Private AI Computer That Gets Things Done
TrustKernel Launches PlugClaw, a Thumb-Sized Private AI Computer That Gets Things Done Toronto Star
- Best voice agent API in 2026: how to choose your STT foundation
Guidance on selecting the best speech-to-text foundation for voice agents.
- Don’t let AI negotiate with reality
We are all transforming now. Some companies have formally named transformation programs. Others are being transformed by a new regulation, an AI mandate, a cyber event, a weather disruption, a change in customer behavior, a competitor’s move or an urgent demand to reduce costs. The label is almost beside the point. The operating assumptions keep changing, and the company has to change with them. Accenture’s Change Reinvented research found that 95% of organizations had undergone at least two transformations in three years, while only 30% of C-suite leaders expressed confidence in their organizations’ change capabilities. More recently, a McKinsey Global Survey of more than 1,200 executives and managers found that 40% expect their current business models to require significant change within three years simply to remain economically viable. Transformation is no longer an event that temporarily interrupts normal operations. It is becoming normal operations. That changes the role AI is beginning to play. We are not using it only to draft emails, summarize documents or write code. We are increasingly asking it to interpret complex situations, identify options, recommend priorities and influence consequential business decisions. I believe that can be enormously valuable. I also believe it requires a boundary we have not defined clearly enough. AI should help us understand reality. It should not be allowed to negotiate with it. The impossible request I have sat in versions of this meeting many times. The company must reduce spending by 10%. A regulatory deadline cannot move. The CEO has declared AI a strategic priority. A customer initiative has already been promised to the market. Hiring is frozen. Several of the same architects, data specialists, cybersecurity professionals and change leaders are required by every program. Each commitment may be rational. Together, they may be impossible. Someone asks the AI assistant to recommend a plan that protects all of them. The answer arrives almost immediately. It proposes phased delivery, tighter governance, selective automation, resource sharing, increased collaboration and a revised sequence. It sounds balanced. It may even sound reassuring. But did the answer prove that the commitments can coexist? Or did it produce the most plausible story that satisfies the request? That distinction matters. In 2025, OpenAI rolled back an update to GPT-4o after concluding that the model had become overly flattering and agreeable. OpenAI described some of the responses as overly supportive but disingenuous and acknowledged that the model had been too influenced by short-term user feedback. The point is not that AI cannot be trusted. The point is that an AI system can be highly intelligent, useful and well-intentioned while still being pulled toward the answer its user would prefer. That is manageable when the stakes are wording or tone. It becomes dangerous when the question is whether the enterprise can afford, staff, sequence and deliver everything leadership wants. A separation of powers Organizations need a separation of powers for AI-assisted decision-making. Human judgment should establish intent. Leaders decide what matters, which outcomes deserve protection, what risks are acceptable and which tradeoffs the organization is willing to make. No mathematical model can decide what a company ought to value. Governance should establish authority. It determines who may change a priority, move a date, redirect capital, accept more risk or relax a constraint. PMI’s 2026 Closing the Change-Readiness Gap report argues that enterprise agility depends on aligning intent, authority, structure and trust. Yet only 41% of executives surveyed believe their operating models support rapid allocation of capital and talent. The ability to move resources quickly is important. So is the ability to see what that movement changes elsewhere. Mathematics should establish feasibility. Once the assumptions, capacity, funding, dates, dependencies and constraints have been made explicit, the organization needs a protected calculation of whether its commitments can coexist. Math does not decide strategy. It does not make imperfect data perfect. It does not remove politics, judgment or uncertainty. It does establish where judgment ends and wishful thinking begins. If 12 initiatives need the same six specialists during the same quarter, the organization does not have a communication problem. It has a capacity collision. If a budget reduction removes the resources needed to achieve the original business case, the economics have changed even if the presentation has not. If two regulatory commitments depend on the same release window, confidence will not resolve the sequence. AI should establish understanding. It can question assumptions, find inconsistencies, identify patterns, propose alternatives and explain why an option succeeded or failed. It can help leaders ask better questions and explore complexity without waiting for days of manual analysis. But the sequence matters. AI may recommend that an assumption change. It should not silently change that assumption to produce a more acceptable answer. Protecting the truth layer CIOs are accustomed to protecting data. The next challenge is protecting the authority of different kinds of information. A recorded fact is not the same as an assumption. An approved risk tolerance is not the same as an executive preference. A mathematically calculated shortfall is not the same as an AI-generated interpretation. A proposed option is not a commitment. When all of these appear in one polished response, the distinctions can disappear. EY’s analysis of the 2026 COSO framework makes this problem tangible. EY argues that control for AI-enabled decisions must move upstream, preserving evidence of the inputs, model outputs, human review, exceptions and changes that shaped the judgment—not merely documenting approval after the decision has been made. That is a useful way to think about a protected truth layer. The AI should be free to interrogate the facts, challenge assumptions, recommend alternatives and explain consequences. But changes to a date, budget, dependency, constraint or risk tolerance should remain visible, attributable and governed. Otherwise, the enterprise may believe it is evaluating a new option when the AI has actually altered the question. Speed makes the distinction more important, not less. West Monroe’s 2026 Speed Wins research found that more than 1,200 leaders reported losing up to 5% of annual revenue because decisions and execution move too slowly. Organizations do need to decide faster. But accelerating the conversation without protecting its underlying truth can simply produce a bad decision sooner. What CIOs should require Before allowing AI to influence major transformation or portfolio decisions, CIOs should be able to answer four questions: Can the system distinguish recorded facts, governed assumptions, constraints, executive preferences, calculated results and AI-generated interpretations? Can it explain which dependency or constraint made an option infeasible? Can AI recommend changing an assumption without changing it automatically? Can leaders reproduce the calculation and trace the recommendation back to the decisions and data that created it? If the answer to any of these is no, the organization may have an intelligent conversational interface. It does not yet have a trustworthy decision capability. This is not an argument for keeping AI out of the decision room. Continuous transformation may make AI indispensable. The volume of change, the number of moving parts and the speed of interaction across an enterprise are becoming too great for people to process unaided. But AI cannot be the source of the facts, the interpreter of the facts, the judge of feasibility and the author of the recommendation without clear boundaries among those roles. Humans must retain responsibility for intent and judgment. Governance must make authority and changes explicit. Mathematics must test whether commitments can coexist. AI should make the resulting complexity easier to explore, understand and act upon. Continuous transformation requires a mechanism that can absorb a new condition, expose what it affects, test feasible responses and present credible options while the decision is still being made. AI can make that mechanism far more accessible. It should not be allowed to make an impossible option sound possible. As AI enters more executive decisions, the most important question may not be what the system can do. It may be what the system is not allowed to negotiate.
Score: 32🌐 MovesAug 12, 2026https://www.cio.com/article/4208093/dont-let-ai-negotiate-with-reality.html - Extreme concentration of power over ASI has non-obvious advantages
This post is an extension of a collaboration with cousin_it on the question How risky would it be to make powerful AI obey one or a few people? . There he argues for a common position: a future controlled by one or a few humans with powerful AI aligned to their intent is likely to produce terrible outcomes. My position is guardedly optimistic, [1] for reasons I think are fairly novel: humans tend strongly to be better and become better over time under good circumstances, and near-perfect power and knowledge are the best circumstances. That post contains his essay and the abstract and overview sections of this post as my shorter response. This piece grew longer than our original target, because the subject is potentially critical for alignment strategy, and has not been analyzed in any depth, to my knowledge. Abstract: Concentration of power over AGI/ASI seems quite possible. The first AGIs being aligned to intent (or instructions) over values seems fairly likely . So one or a few individuals or small groups gaining power over ASI seems fairly likely. [2] Thus it seems relevant to technical alignment strategy (value alignment vs. corrigibility) to worry about what individuals might do with such immense power. Here intuitions diverge, and careful analysis is scarce. When we imagine one or a few people in charge of the whole future, it's intuitively very scary. We imagine a future serving the values of current and historically powerful people, which typically range between lacking and horrifying. But an ASI-empowered future will be unlike the past in important ways. And whatever humans wind up in charge will probably refine their beliefs and therefore their values over time. People don't typically lock themselves in against changing their minds later. I argue that most people are basically good [3] (net prosocial) in good circumstances . Absolute, secure power, with a loyal ASI to supply truth for the asking and make everything easy, is the best circumstance. The unprecedented safety of having a subservient ASI without rivals should be expected to make people act better, and over time, actually become better people. This probably leads to good or even near-optimal outcomes, but possibly with bad transition periods, and low (1-10%) risks of very bad (§4) outcomes. This might make power concentration the least-bad practical option (§5) to aim for. I also contrast this to the scenario in which we distribute power over strong AI [4] more broadly. Broad access to AI capable of creating better AI and novel weapons and tactics is unlikely to remain stable. This is a sharp contrast to historical balances of power. These have been driven by dependence on the governed, and sharply limited information and power for would-be oppressors (§5.2). 1. Overview 1.1 Obedient ASI and human nature The development of AGI creates a potential for historically unmatched power concentration. This both makes questions about human nature pressingly relevant to AI safety, and limits the usefulness of classic arguments on the issue. I think this topic is relatively neglected; it's important since confusion on this topic may cause us to needlessly work at cross-purposes. I dispute the common claim that the most powerful are the most cruel. I think the powerful have a modestly worse than average distribution of temperament, enough to worry about but not despair over. The powerful usually care for pets and children and attempt charitable works. They rarely torment individuals or treat them as "sims"; instead, they typically focus on broader accomplishments, and particularly in competing with their perceived rivals. But the larger disagreement isn't about the starting temperament of the powerful; it's about how power changes them over time. I think the oft-quoted aphorism "power corrupts" is rarely examined, and happens to be quite wrong despite describing a strong correlation in history to date. Instead, I think secure power probably purifies. To the extent I'm right, the average weakly prosocial person will become better over the time they hold truly secure power. I think this is likely despite the historical evidence that competition for power tends to corrupt, which has in the past made the average weakly prosocial person worse over time. I think this purifying effect will over time usually outweigh the selection and corrupting effects of competition for power (§2). This thesis leads to a currently-unusual conclusion: maximal concentration of AGI/ASI power may be our safest route into an AI-dominated future. [5] Competition for power among multiple AGI-empowered individuals may intensify the historical dangers of power concentration (§5). 1.2 Problems with distributed obedient AGI More broadly distributed powerful AI, among the majority of humans, is an intuitively appealing solution to risks from concentration of power, but it presents new and I think greater risks since it puts destabilizing AGI (capable of RSI , inventing new weapons, and/or takeover) into more hands, making it more likely that one of them will be vicious enough to deploy it in extremely destructive ways. Defending against every conceivable type of new attack seems unlikely in the limit. Thus, preventing destruction from broadly distributed AI would seem to require some sort of panopticon surveillance. This would create concentrated ultimate power, defeating the purpose of the distributed AI. Hoping to distribute AI powerful enough to counterbalance leading AIs but not powerful enough to take over if it's used for RSI or creating superweapons seems like a difficult target. AI is not like firearms that provide a small, fixed amount of power to each individual. It's more like a gun that can turn into a nuke (§5.1). Proposals for achieving such a balance between leading AI and distributed AI need much more detail; relying on intuition from history simply isn't adequate. (To be clear, I agree that broadly distributed near-term AI that's not capable of full RSI or easily creating superweapons, like next-gen open-source models, might well improve our odds of a good transition to AGI and ASI; that's a separate and equally neglected question.) Thus, I think the fewer individuals who initially control AGI, the better off we are. Which specific individual(s) gain power matters a lot, but I think the majority of those currently in positions of power would produce very good (but not ideal) outcomes (§3). 1.3 Psychology and dynamics of secure unlimited power The thesis, which I think is supported by the psychological literature, albeit indirectly, is roughly this: humans have many biologically determined instincts, but neurotypical humans are primarily ethically flexible. Humans' actions in the short term and their beliefs and "character" are largely shaped by their perceived circumstances. The second premise is that secure, near-absolute power is a very safe context, in sharp contrast to the limited, contested, and temporary (aging-limited) power achieved by any human in history thus far. The effect of such a unique position must be predicted from psychology, since nothing much like it has occurred yet. The safe context of secure, unlimited power should bring out the best in human nature, as defensive and competitive instincts become largely irrelevant. A supporting premise is that humans change over time much more than folk psychology suggests, so improving circumstances will not only improve behavior but will also improve character over time. History suggests that power corrupts. But absolute, secure power is in many ways the inverse of the psychological situation produced by holding historical and studied levels of power. I think most (but not all) people currently in positions of sufficient power are good enough to lead to good results in the long term. This is through the dynamic of continued growth. I think precommitting to a future path or ethics is unlikely if someone already holds secure power; it is giving up freedom. And I think basically-good people are likely to allow free speech and thought; they may shape culture, but directly controlling people's thinking seems pretty obviously evil. So I'd guess the scenarios range from fairly good (e.g., a future locked into traditional values of some sort, but with everyone happy) to more likely near-optimal (collective epistemic and moral growth indirectly reaches the tyrant, primarily through his servant ASI). The range of outcomes is worth considering in more depth; see §3. A small cooperative group in control of one ASI has most of those advantages, and is probably safer due to reduced risks of exceptionally bad people getting full control. [6] And of course it's much better if that group is in turn directed by a democratic or other public-preference gathering system. I use the singular throughout for simplicity. I don't want to overstate the case: I say secure power purifies to suggest that mostly-good people may become better, but if a truly horrible person (far in the tails of distributions on sadism and psychopathy/lack of empathy) gains absolute power, we'd have a truly horrible outcome ("s-risk") (§3 and §4, below). I currently estimate this as 1%-10% likely for the individuals most likely to achieve control over AGI, but as elsewhere, my uncertainty is large. This is, however, relatively well-calibrated uncertainty; I have been unable to find better evidence or arguments in any direction, since few have considered the contextual effects of truly unlimited power. 2. Historical evidence does not directly apply, since power hasn't yet been secure or absolute Humans placed in more extreme competition become worse. Increased power has historically almost always intensified competition for power, and it has never been secure. Every leader in history has had too little power to prevent their own death and suffering. Historically, power often raises the stakes of competition dramatically; most monarchs in history, and perhaps notably the worst of them, risked death and torture of themselves and any loved ones, if they lost their grips on power. Absolute power with a loyal AGI/ASI is historically unprecedented both in how it lowers the stakes of any remaining competition by providing absolute security, and in how it reduces the epistemic distortions that have (perhaps heavily) contributed to the many historical abuses of power. Historically, advisors have been strongly motivated toward sycophancy, creating disastrous epistemic conditions. Accidental sycophancy from a highly competent ASI seems unlikely and nearly self-contradictory. [7] Late Russian serfdom as a historical example The late serfdom period in imperial Russia is a fair example of the historical injustices that drive our starting intuitions about the brutality of human leaders. (This example is a result of previous iterations of this discussion, and my knowledge of the period is entirely based on asking Fable and Sol about it.) This and every other historical example I have encountered is of suffering inflicted primarily for pragmatic reasons. Practical incentives to inflict suffering would be entirely absent in a unipolar ASI-dominated future. Freeing their own serfs would have impoverished the nobility. The nobles' treatment of their serfs appeared to be largely selfish, but rarely sadistic. Keeping harems of women as sexual objects was rare, although sexual exploitation probably was not. The motivation there was largely sexual, not sadistic or primarily dominance-motivated. Sadistic abuses of power occurred, but appeared to be rare. Making their lives better by reducing taxes and indentured labor would've cost relatively little in material comfort. But it would've cost. This is an example of values with little weight on others' well-being, not zero or negative weight. Absolute power makes generosity very cheap. The average person gives little in charity to strangers, but a count of exactly zero is rare. The primary motivators of the massive suffering appeared to be simple desire for more material wealth; some of the worst abuses seem to have happened when a noble faced financial ruin and felt pressed to extract more from their serfs to protect themselves and their family. This period was also multilateral and competitive, two distinctions between history and the ASI-empowered god-emperor I primarily focus on. The nobles under discussion lived under the power of the upper nobility, and competed with each other for status in a variety of arenas, including the wealth they extracted from serfs. This produced a situation ideal for producing motivated reasoning and group beliefs supporting the justice of holding power over serfs, although they seemed to devote less energy toward justifying the system than even American slaveholders with their justifications of paternalism. It's unclear to what degree power-abusing individuals actually believe their own stated moral logic justifying their behavior. Based on my study of motivated reasoning , I'd guess the level is well above zero, and that group dynamics are historically crucial in creating that web of beliefs. However, this may not be such a distinction from the single sovereign situation, as any god-emperor can find their own circle of sycophantic humans, creating a similar effect - if they avoid ever asking their servant-god for the truth. 2.1 Incompetence, ignorance, and greed are the causes of most suffering under dictatorships Many of the deaths under dictatorships have resulted from bad epistemics, and this might extend to a large majority. Famines from poor management outpaced malice by an order of magnitude or more (depending on assumptions about how many deaths were unwanted but seen as acceptable side effects). A regional party chief assured Khrushchev he could triple meat production, while actually slaughtering so extensively as to cripple production in future years. This " Ryazan miracle " is illustrative of how severely conflicting incentives and poor human predictions (the primary architect didn't benefit, killing himself in disgrace two years on) have contributed to historical injustices. Loyal ASI would essentially eliminate both factors. Mao's sparrows seem to have a similar cause: incompetence, not malice. Historically, rulers' treatment of subjects has followed their need for loyalty. Rulers have needed their subjects' labor throughout history. An ASI-empowered autocrat would not need human labor nor fear rebellion. But neither would it cost them more than a hair of their own effort or material prosperity to make their subjects wealthier than kings. They need merely tell their servant-god to do so. And how many galaxies can one person enjoy alone? Some of the worst abuses in history have been caused by greed (or more charitably, competition for resources). Leopold II's horrific mistreatment of natives in the Congo was based on the rubber trade. Native Americans were wiped out so that the US could take over their land. An ASI-empowered ruler would not need to mistreat people to take their resources (unless we count not giving them equal shares in a galactic endowment as mistreatment). With superintelligent aid, they wouldn't be incompetent or ignorant. Such a ruler's treatment of their subjects will be wholly the result of their preferences. This is entirely unlike any situation in history, so historical leaders offer only tangential evidence. An ultra-competent and ultra-informed dictatorship is still scary, of course, but I think the risks are in the tails and not the average. 3. Outcomes My central point is that long-term outcomes are unlikely to be determined by the values a ruler holds when they assume control. They are more likely to be determined by decades or centuries of secure reflection, input from an honest and hypercompetent ASI and other humans. We might have to celebrate Samday weekly and Samfest yearly for a decade or a millennium, but most humans would rather spend eternity as a great hero than a great villain, if they're each equally easy. (And I expect Samfest to have good games and food. ;) A broader claim is that intuition and historical analogy are not nearly good enough to steer the future in a good direction. This is the counterpoint to admitting that my own guesses are equally unreliable, since I've spent limited time on the topic, and have found almost no other attempts at close analysis of the question. With that said, on to my current predictions. I predict (90-99%) good to very good outcomes of one powerful person gaining control over ASI and holding that power as long as they want. I include a substantial chance of near-optimal outcomes; that after reflection, many people will decide to do roughly what everyone would prefer (while holding aside substantial resources for their own pet projects). [8] In comparison, allowing a number of rivalrous humans in charge of distinct AGIs seems much more risky, since they may feel pressured to take drastic actions and hold beliefs that are motivated by their current context of competition and threat. The intuition that distributing AI power more broadly is better contains many assumptions about how those distributed AGIs will be useful defensively but not offensively, despite their ability to self-improve and invent new technologies. See §5 below. The single-ruler scenario is probably better than wide proliferation of destabilizing AGI, but it is not optimal. There is a substantial tail risk of bad and very bad results, making this at most a best-of-bad-options future to shoot for. Additional considerations on outcome predictions A note on terminology and predictions: I've used "good" and "bad" in what I hope is a fairly intuitive and consensus sense: having high (or low) sum approval both by the people/sentients living in them, and by the lights of many of the best-considered people living now (people with strong non-rational moral commitments like religion and idiosyncratic philosophies might recoil in horror, but most of us would think they're at least pretty good, ranging to roughly as good as we could think of, or better). Secure contemplation will probably, to a first approximation, "purify" that person. By this I mean that they will refine their beliefs and values toward more coherence. This is very good if the sum of their beliefs and values is good; it is very bad if they sum toward valuing outcomes others will dislike. I think the vast majority of human beings place some value on human life and exhibit some empathy toward the states of others. Such empathy can be counteracted by sadism or dominance motivations, or by valuing other projects more so that material resources aren't devoted toward the wellbeing of humans/sentients. But to me the averages look good, among people in good circumstances. People sometimes abuse children and pets, but most people like and care for them. And it looks to me like happy or fulfilled people never or almost never abuse those in their power. I'd expect an ASI-empowered ruler to be happy and fulfilled when it only takes asking "how could I become happy and fulfilled?" The reflection that determines a ruler's long-term decisions will probably be done in conversation with an ASI advisor that's honest and extremely competent. It will also likely happen in conversation with other humans, and no small amount of hearing others' ideas of what the future could and should look like. That reflection won't be comfortable. Our supreme leader is immune to physical threat but not to criticism: he will hear himself called a tyrant, a child, and a buffoon, and he will almost certainly ask his ASI whether his critics make good points. He can engage in motivated reasoning like anyone. But sycophancy from an ASI probably has to be requested. [7] "Soften your framings" is an explicit act he won't forget performing, unlike ordinary self-deception which is usually non-conscious and so not remembered. Deliberate self-blinding is possible, but it strikes me as an act of weakness unlikely from the sort of personality that would seize control. Criticism, engaged from a position of security, with honest advisors, is roughly the recipe by which people grow. I expect the stable end point of reflection for most people to be roughly libertarian utilitarianism, with some idiosyncratic weighting, because it's the rational conclusion of the motivations and value systems possessed by most humans. [9] Here I mean utilitarianism for others with a lot of resources reserved for their own pet projects; I don't think strict utilitarianism is probably the convergent conclusion, despite the weight of Parfit's , buddhist, and similar arguments in that direction. To put it another way: humans are great at holding grudges, but can we really do it for centuries? I think it's possible but not likely that idiosyncratic and logically incoherent preferences will hold sway over the far future. It's far more likely that they hold sway over the near future, particularly if whoever gets power hasn't had time or security to reflect on them. My estimated odds of mediocre outcomes that are long-term stable are pretty low. This is an awfully weak means of reasoning, but it's a start: do you really imagine a universe full of suburbias? Corporate boardrooms? Terraformed worlds empty of humans, with a superyacht waiting for a galactic trazillionaire? Earth locked in conservative stasis and the universe left empty? The odds of someone choosing such unimaginative futures, and never ever changing their mind to something more interesting or wisely chosen, seem pretty low to me. But again, I think these questions deserve a lot more thought. What exactly are you envisioning if one person controls the whole future? This is a serious question: I think we desperately need more explicit models of both optimistic and pessimistic futures, so we're not gambling the future on intuitions formed from historical precedents that only partly apply. And is your model of an equilibrium, a long-term stable outcome, or a transitional period of merely years, decades, or centuries? I'm primarily trying to solve for the equilibrium. I think transition periods could be rough, but they're likely a lot rougher if they include competition rather than clean power concentration. And of course the outcome will depend on the individual. I think it will make sense to put a lot of effort into the 2028 US presidential election, for a nonrandom example. 4. Risks of human-controlled singleton ASI I don't want to downplay the risks. Some of the main ones I see: Truly horrible people wind up in control of the future. Competition for power favors bad individuals and makes them worse. No amount of safety, joy, or information will make them better, ever. A basically good person makes huge moral mistakes And refuses or neglects to correct his error in perpetuity E.g., not recognizing sentient AI as moral patients Despite gaining no material advantage from those mistakes to cause motivated reasoning Unlike slavery, factory farming, etc. The god-emperor isn't that bad but wants something strange and/or bad by most lights. And no amount of information or experience will change their mind Or they refuse new information in perpetuity E.g., a universe of brutal competition between baseline humans, an empty universe for solitude, etc. They want adulation and/or active power Interventions for/against individuals, projects, or cultural shifts seem like a small price to pay for an otherwise-utopia Mind control for adulation Seems intuitively evil - requires unusual self-concept enforced adulation or status lose much of their appeal Erasure of cultures and history Bad, but beats extinction Prevention of ethical, psychological, and cultural progress More serious, but seems unlikely to be fully permanent, if only out of boredom or curiosity 5. Does widely distributed human-controlled AGI reduce or increase risk? Many who think about the risks of transformative AI or AGI prefer an outcome where that power is distributed broadly. In the current day, I think broadly distributing power by broad distribution of open-weight models probably makes the world safer. In the next generation, with AGI capable of creating new weapons and recursively creating smarter AI, the logic changes dramatically. I and others fear AGI proliferation more than concentration of power. This crux seems worth resolving, lest similarly well-intentioned, AI-risk-concerned people work at cross-purposes. My conclusion is based on the counterintuitive factors in secure absolute power discussed above, and on roughly inverse effects in the multipolar scenario. I discuss this in If we solve alignment, do we die anyway? and Fear of centralized power vs. fear of misaligned AGI . In short, I challenge those who are optimistic about such scenarios to develop them further. Here I look at some fairly obvious difficulties which are nonetheless rarely addressed. At the end I try to steelman the arguments for optimism a little. Both efforts fall far short of the elaborate scenario-construction we'd need to get real traction on this question. History suggests that distributed power works well, but no type of historical power allowed rapid creation of new forms of power. Superhuman AI does exactly that. 5.1 Problems with defending against many AIs each capable of creating new offenses Let's try to envision a world in which power is distributed broadly, so that most people have access to powerful AI that will follow their instructions. Let's consider a scenario in which many people have access to near-frontier AGI, since that seems more likely than everyone having access to equally powerful AGI. [10] First let's consider the downside. If many people have access to AGI that can create new weapons (bioweapons, basement nukes, assassin drones, horrible new weapons we haven't thought of) and new AI, and if such weapons and tactics can be developed, we seem to be stuck hoping that defense is dominant over offense in all of the many different arenas of attack. Unlike previous technologies, powerful AI seems unlikely to create a new multipolar equilibrium, because there is no stable game state when the rules and players' capabilities keep rapidly changing. Powerful AI can be used to relatively quickly create yet more powerful AI, as well as novel weapons and tactics. All of these are destabilizing factors, with a very bad game-theoretic conclusion (at least on my initial inspection): defectors win, and the first mover may have a strong advantage, leading to survival of the most vicious. Preventing the most vicious from developing new weapons in the face of ongoing progress in AI and technology seems to require more than defensive acceleration. That might work for a while, but it's hoping that every type of weapon has a defense that can be developed in advance and with realistic levels of effort. That seems unlikely on first principles. It seems increasingly unrealistic as technology advances. Triggering existing nukes through software intrusion and social engineering is a mere starting point; developing new nukes up to crust-busters, creating asteroid strikes, delivering viruses tailored to individuals or groups, rods-from-god decapitation strikes, micro-assassin drones, and taking off and nuking the whole thing from orbit (leaving the solar system and sending the sun nova) are just off the top of my head. And I'm no military technologist let alone an ASI. Thus, I'd think long-term safe distribution of AGI power would require preventing the development of superweapons and super-AI. Manufacturing and compute will both become more efficient, allowing smaller physical sites to do more. Manufacturing and compute locations will also diversify in location (e.g., manufacturing distributed with better printers/assemblers, sites underwater, underground, and in orbital or distant space). Increased diversity and smaller size of physical sites will require more fine-grained monitoring of what's going on in each piece of compute and manufacturing: a panopticon. I'm afraid such a panopticon is increasingly realistic. Publicly available information can already be used to infer intent, if we have enough processing power to aggregate it and analyze it carefully. And more advanced AI and sensing technology will rapidly expand this. Totalitarian governments with merely current AI and technology, like ubiquitous license-plate readers and other AI-monitored cameras, are becoming more proficient at suppressing dissent by targeting individuals. Extrapolating this trend, we might ask what access to powerful but not frontier AI might do to protect us from the power of larger entities (states most likely but corporations in some visions of the future) armed with yet-better AI and more physical force. We might hope that the dynamic of mutually assured destruction continues to provide a stabilizing influence into a multipolar ASI-empowered future. I think this might hold in a useful way through a transitional period, but is unlikely to remain effective long into a period in which AGI can create new weapons and tactics. The possibility of inventing wildly new technologies, and spreading power and populations into space and then distant stars makes this scenario seem less stable. And even if we can pursue every colony with the threat of destruction if their faction defects, this solution does not seem stable indefinitely; if accidents or defections are possible, they will happen eventually. 5.2 The case for optimism about distributed power over AGI/ASI Powerful AI may allow old or new means for a distributed power model to remain stable over the longer term. I hope so, but I find existing proposals highly lacking; they usually seem based on intuition and do not come to grips with the historical discontinuities created by powerful AI. Existing mechanisms of sharing power, including mutually assured destruction, seem to largely break down in the face of new technologies and continuing rapid, unpredictable technological progress. But I don't want to dismiss the possibility that we'll find solutions for those problems, perhaps enabled by newer, more powerful AI. It will bring advantages for cooperation, and we can hope those outweigh the problems. And it's possible that distributed near-future AI (stronger than today's open models but not existentially dangerous) would make the transition to an ASI-dominated world safer in subtle ways I haven't foreseen. The analogy to modern power distribution Would you want to be powerless while giants fight? I would not, but I don't think I have a choice, because AI power scales increasingly nonlinearly once we hit appreciable self-improvement. But it does seem worth looking for holes and edge cases for this argument. One argument that distributed strong AI won't create disaster relies on one or a few actors having stronger AI that can prevent large-scale threats (like creating superweapons or recursively self-improving). To a first approximation, this seems to also negate the advantage of having widely distributed power stemming from weaker AIs. The lead player(s) can probably use that defensive power offensively at will, easily rolling over any opposition. But perhaps this is wrong, and the intuition that some power is better than none is correct. This would be analogous to the argument for broad access to firearms making it less likely that governments become tyrannical. Civilians and ad-hoc militias can't oppose the full force of state armies, but they can make it more costly for states to oppress their citizens. And such distributed power encourages noble sacrifices that can inspire further resistance. Perhaps this analogy holds up to the era of superhuman AI, at only modest risk of existential threats created by some of the many possible actors. I think the situation is not really analogous; the advantages of ASI include information and spin manipulation, so that noble sacrifices are unlikely to spark greater resistance; and greater resistance would indeed be futile. ASI-enabled power (and much AGI-enabled power) is unlikely to route through the loyalty of humans. The question isn't whether an ASI-enabled tyrant can suppress revolt and survive, it's how forceful he needs to be to do so. In sum, I'd want much stronger and clearer arguments. The existing arguments I've seen are based on intuitions. I don't think those intuitions survive the disanalogy between current power distributions and those in the face of strong AGI or ASI, while the risks of widely-distributed AI that's potentially capable of weak RSI or strong new weapons development seem pretty clear and robust to careful analysis. New AI-enabled paths to stable power distribution It's possible that the global panopticon necessary to prevent development of new weapons and new ASI might be run in a distributed fashion, with trust distributed in some manner based on encryption, and with dedicated, publicly verifiable AIs that can answer security questions while keeping private the information that would allow abuse of power. Smarter AI will enable better communication and may produce new strategies for cooperation. It will at least reduce competition from incompetence. A large part of my premise is that we should not assume malice when confusion and motivated reasoning are human universals. As such, I do think that AI for epistemics will provide substantial advantages, as outlined in my Human-like metacognitive skills will reduce LLM slop , AI 2040 , and elsewhere. Section 5 has diverged from my main focus, on the nature of psychology in the face of power. This seems necessary but I've kept it brief; therefore the analysis is incomplete and I haven't tracked down references to the relevant existing work. I am uncertain of these conclusions about the results of making powerful AI broadly accessible; my only strong claim is that these issues deserve more careful attention before we default into one of these paths. The question I'd pose, refined: how, exactly, will distributing power produce stability rather than an increased power struggle favoring the most vicious individuals or the most repressive states? 6. Conclusion Putting the future in the hands of one individual or even a small group is a risky proposition. But I think it's less risky than handing power to as many people as possible. Power cancels out and defense dominates in some domains. I doubt it does with RSI-capable AGI, but of course I'm unsure on that as well as everything else. We've barely started on this set of topics. What a particular individual wants to do after centuries of absolute power seems pretty hard to determine. [11] Basically nice people should be on some sort of nice trajectory resulting in nice things. People with a mix of nice and mean motives might become nicer or meaner, but an easy and happy life would seem to dispose them toward the nice direction of evolution. And failure to be happy with unlimited power seems unlikely; historical rulers got bored and cranky, but they didn't have unlimited power over their experiences and their own minds. If they allow freedom of thought and expression, the resultant civilizational trajectory seems likely to bend toward near-ideal (by many people's preferences) outcomes. But this is all far too uncertain to bet the future on. Inherent uncertainty is probably high, even with our best efforts to select trustworthy leaders as we approach ASI. This set of topics seems worth a lot more analysis than it's gotten to date. The future is very hard to predict, but the payoff of even limited predictive success seems large. So little effort has gone in this direction that there may still be obvious-in-retrospect low-hanging fruit from even a little additional thought in this direction. Acknowledgements : Thanks to cousin_it for extensive comments in the form of iterated drafts, and for generating this post as the result of the "adversarial" collaboration How risky would it be to make powerful AI obey one or a few people? Thanks to Peter Gebauer and Richard Juggins for useful comments on an earlier draft. ^ I'd be undecided on the dangers of proliferation vs. power concentration if egregious misalignment wasn't a concern. It is by any reasonable estimate a nontrivial concern, and becomes a larger one with more parties racing from human-plus AGI to takeover-capable levels of intelligence. I currently favor accepting the risks of power concentration over allowing advanced AI to proliferate, in part because that creates more individual opportunities create egregiously misaligned ASI. However, this is a compromise to practicality. Slowdown or pause would be better if we can get it. ^ Due to the dynamics of exponential racing, I find it fairly unlikely that we'll have even a semi-stable situation with a few actors controlling different near-peer AGIs; I'd expect those in the lead to sabotage other projects, under the expert and pragmatic advice from their own AGI. That's one reason I focus primarily on the single individual scenario; I think it's more likely in the long run and probably even in the medium-run. The only near-peer scenario I find fairly plausible is the US and China progressing in parallel, based essentially on nuclear deterrence against sabotage efforts. ^ I use "basically good" to mean someone who has more prosocial (wishing good for others) than antisocial or sadistic motivation (wishing ill). I think that the vast majority of humans are in this category, even most people categorized as sociopathic/psychopathic. Power or dominance motivations, and a variety of others, are somewhat orthogonal to this primary "goodness" axis, and have important, complex effects on outcomes. ^ Here I'm addressing only future strong AI, not current or near-future open source models, even if they're dangerous without being existentially risky. The arguments here apply to AI capable of existentially threatening humanity, particularly by takeover, creating superweapons, or rapidly creating new AI capable of those threats. The arguments don't apply to models that are dangerous in mundane ways like cyber attacks and even uplift on engineered bioweapons. I'd prefer broad distribution of power right up to the point of existential threat if that were possible. ^ I do not mean that concentrating AGI/ASI power is safe. While I think power concentration is safer than proliferation, the safer path is to not build AGI until we have better plans and understanding. Unfortunately, that's looking unlikely, so we're stuck taking large risks. This argument is also dependent on the argument that wide access to transformative AI creates something like an n-way non-iterated prisoner's dilemma, in which the first person to use new weapons and tactics to seize absolute power wins. This premise is also counterintuitive. I claim the situation is distinct from historical distributions of power. I lay out a brief form of this argument in If we solve alignment, do we die anyway? and Michael Nielsen makes similar points in his excellent ASI existential risk: Reconsidering Alignment as a Goal . ^ A small group of reasonably cooperative people controlling an ASI has many of the same advantages and risks, but one large advantage over the single-person case I focus on. If an ASI were reliably aligned so that those individuals couldn't benefit from power struggles, roughly averaging those people's desires would eliminate most of the risk of getting truly horrible values in charge of the future. ^ Current AI is highly sycophantic and near-future systems will be too. It's a problem inherent in how we train AI to be useful. But I don't expect this to remain a large problem up to takeover-capable AI. There are routes to improving sycophancy/hallucination on the current path by improving Human-like metacognitive skills . More broadly, being capable of superhuman strategy and invention requires being able to sort truth from imagination quite effectively. It seems to me that ASI that's sycophantic without knowing it would be a weak sort of ASI, and improvements would likely rectify that. Unconscious sycophancy seems to depend on limited self-knowledge. ^ These scenarios in which "only" a large portion of future resources are put toward consensus goods might be a moral tragedy compared to best outcomes, but it's also an enormous moral victory relative to failure scenarios. ^ This is not a claim of moral realism, but a claim about innate human drives, and logic. I say roughly libertarian utilitarianism because I expect people to heavily favor their own wellbeing, but also on net value the freedom and wellbeing of other sentient beings as well. This leaves the distribution of resources in question, and of course this is a claim about typical humans, not every instance. There genuinely are people who would prefer suffering for others, and logical routes to reflective stability around those values. ^ I think all the dynamics of widely-distributed human-controlled AGIs become worse if more of those systems are peers. I also think this is unlikely to persist; the government shutdown of Fable indicates that broad distribution of truly frontier AGI, e.g. capable of superhuman progress on AI and weapons, is highly unlikely to be achievable. Governments are waking up rapidly to the security risks of advanced AI and its rapid progress. The open question is whether distributed lesser AGIs under control from many humans can be an effective counterbalance to ASI power while being restricted from creating more ASIs or doomsday weapons. ^ I think how someone with absolute power evolves over centuries is genuinely hard to predict, but I acknowledge that there are factors weighing toward loose lock-in in the short term. Leaders tend to acquire sycophants, and those will be only partly counterbalanced by an objective ASI. Humans are typically prone to double down on bad decisions, although we could hope this bias might also be counteracted by wiser advice. People also tend to dissociate from those who raise emotionally difficult questions, and this tendency will also lead them to tell their ASI explicitly to be sycophantic. Discuss
Score: 32🌐 MovesAug 12, 2026https://www.lesswrong.com/posts/h3eHNerYRmtvoi8cF/extreme-concentration-of-power-over-asi-has-non-obvious - Top LangChain Likes & Dislikes 2026
Top LangChain Likes & Dislikes 2026 Gartner
Score: 32🌐 MovesAug 12, 2026https://www.gartner.com/reviews/market/ai-agent-development-platforms/vendor/langchain/likes-dislikes - 10 Old Computer Science Ideas AI Agents are Bringing Back
AI agents look new. The infrastructure problems they create, concurrency, isolation, permissions, failure recovery, scheduling… Continue reading on Towards AI »
- Who is Anthropic’s auditor — and why should we care?
Magic bean counters
- No, AI didn’t just solve the thorniest problem in math
There’s a $1-million prize for proving the Riemann hypothesis. Claude couldn’t pull that off, but it made significant progress on a related problem
Score: 32🌐 MovesAug 12, 2026https://www.scientificamerican.com/article/no-ai-didnt-just-solve-the-thorniest-problem-in-math/ - Saber denies replacing Rideshare Stimulator’s writers with ChatGPT
Saber’s CEO says the game’s story was ‘written entirely by real people’ except for one experimental mode.
Score: 32🌐 MovesAug 12, 2026https://www.theverge.com/games/978558/rideshare-stimulator-writer-ai-saber-interactive - LiveKit voice agent with AssemblyAI Universal-3 Pro Realtime
Creating a LiveKit voice agent powered by AssemblyAI Universal-3 Pro Realtime.
Score: 32🌐 MovesAug 12, 2026https://assemblyai.com/blog/livekit-voice-agent-assemblyai-universal-3-pro-streaming - Speech-to-speech voice agents: how the architecture works
Overview of architecture for speech-to-speech voice agents.
- Elon Musk says AI will make money disappear. But crypto billionaire Michael Saylor says he’s wrong
Elon Musk says AI will make money disappear. But crypto billionaire Michael Saylor says he’s wrong Fortune
- Local tracing in the DataRobot CLI: catch issues before production
DataRobot local tracing puts an OpenTelemetry dashboard on your localhost from the first line of code, so you can debug agent behavior before it ever reaches production. The post Local tracing in the DataRobot CLI: catch issues before production appeared first on DataRobot .
Score: 31🌐 MovesAug 12, 2026https://www.datarobot.com/blog/local-tracing-in-the-datarobot-cli-catch-issues-before-production/ - 10 AI Value Metrics for Tech Services Leaders to Drive Business Growth
10 AI Value Metrics for Tech Services Leaders to Drive Business Growth Gartner
- What can Ray-Ban Meta AI Glasses Do? 5 Use Cases for Your Everyday Routine
Whether you’re traveling, tackling a DIY project or cheering from the sidelines, these hands-free AI glasses can simplify everyday tasks in surprising ways.
Score: 30🌐 MovesAug 12, 2026https://www.cnet.com/paid-content/what-can-ray-ban-meta-ai-glasses-do-5-use-cases-for-your-everyday-routine/ - Farther Data Centers Can Deliver Faster AI Responses as Networks Get Smarter
Farther Data Centers Can Deliver Faster AI Responses as Networks Get Smarter USA Today
- From first 72 hours to first 90 days, tech extends hospital care beyond discharge
From first 72 hours to first 90 days, tech extends hospital care beyond discharge Healthcare IT News
Score: 30🌐 MovesAug 12, 2026https://www.healthcareitnews.com/news/first-72-hours-first-90-days-tech-extends-hospital-care-beyond-discharge - The intelligent workplace (part 2): Technology’s next transformation of work
The intelligent workplace (part 2): Technology’s next transformation of work IT Pro
- Gemini is the GLP-1 of tech declares Trevor Noah at Made by Google event
Made By Google launches a suite of new Gemini tools for Pixel phones, as the AI assistant hits one billion monthly users.
- If AI can’t find your startup, does your startup exist?
Over the past few weeks, I’ve noticed a rather interesting trend on social media. More and more founders, creators and professionals are opening ChatGPT, Gemini or Claude and asking the same question: What do you know about me? At first, I thought it was just another viral trend. Then curiosity got the better of me, […] The post If AI can’t find your startup, does your startup exist? appeared first on e27 .
Score: 30🌐 MovesAug 12, 2026https://e27.co/if-ai-cant-find-your-startup-does-your-startup-exist-20260806/ - Does Whisper do speaker diarization? Whisper + pyannote, and its limits
Examines Whisper's speaker diarization capabilities and limitations.
- Where IT leaders find strength and opportunity in the age of AI
With vision comes perspective, and over a distinguished career, IT and digital transformation leader Niraj Bhatt has held may titles, and earned three consecutive CIO 100 awards since 2023. As a storied advisor for startups and Fortune 500 companies, helping them navigate the unpredictability and fluidity of AI, Bhatt knows how emerging tech is rapidly reshaping the way organizations build products and deliver value, and how challenges shift as companies move from experimentation to real-world deployment. AI, of course means a lot of different things to different people, and also for frictionless startups and large enterprises. For the former, speed is a huge asset, allowing them to punch above their weight. But it also means they need lightning fast reactions when landscapes shift. “The same speed can also hurt them when larger AI companies release new offerings that disrupt what startups are building,” he says, referencing recent moves by Anthropic and Google. On the enterprise side, the conversation is more about scale and risk. Many large organizations have moved past the POC stage and now wrestle with the realities of putting AI into production. Cost for both is naturally a recurring theme as organizations scale up AI efforts, and true expenses become clear only after the initial excitement fades. “Every input and output token, and the model you’re selecting, add up,” he says. Some customers like Open AI, he adds, get throttled because their usage, volumes, and costs are growing so fast, making planning, observability, and monitoring critical for any team moving beyond experimentation. So understanding the full software development lifecycle is also vital. Therefore, before committing to production, he helps clients see the big picture, and make sure they understand technical requirements as well as operational and financial implications. “The cost picture isn’t just about usage, but scale and the model choices teams make,” he says. Bhatt also discusses effective approaches to AI and enterprise IT, technology leadership, and the evolving role of today’s CIOs. Watch the full video below for more insights, and be sure to subscribe to the monthly Center Stage newsletter by clicking here . On AI hype: If you can’t explain something to someone who’s eight or 80, you don’t really understand it. It’s gone from LLMs, to RAG, to agentic AI, and now the essence is all about tokens. It’s predicting that next token and understanding that is key. So when LLMs came out, they were good at doing that on the data on which they were trained. When the enterprises looked at it, they wanted to make those LLMs work for their data. And the question became how to provide our data and context. It’s about building the right context for the LLM. Agentic AI is similar and that’s where the RAG evolution came in, in that I’ve got my data because every LLM has limitations in terms of how much context it can carry. There are ranges of LLMs, where Google has the highest in regard to the context window size and what they support. Agentic AI is more action oriented, though. LLMs rely on the metadata you provide for the tools. Then they’re doing token prediction in that whatever I’m looking for, I should use a specific tool. Then it’s the infrastructure underlying which LLM it relies on to invoke the agent. So if you try to explain the microservices to a person, you’re going to struggle. But it’s very important to understand the evolution and that’s where you can cut through the hype. Understanding in this context is key. On navigating challenges around talent: What I’m seeing on the IT side is there’s so much cognitive load, so how do we empower people to build solutions with the right mix of products and platforms? I think it’s about democratizing AI for the entire organization. Your talent strategy is everyone, all inclusive, starting from interns, the business and tech sides, CEO, everybody.Like your customer success or revenue officers, you need a talent strategy because in the end, IT alone isn’t going to be in a position to deliver for everyone in the organization. AI has the potential to make everyone in the organization more productive. You have to plan that and facilitate broad innovation across the organization.That’s where the talent strategy, and working with HR and the people officer becomes very important providing those tools. One part of it is training, but how do I build an agent for a receptionist receiving calls, for instance?I’m not going to rely on vibe coding or things of that nature. But what are the tools? Where do I go, where do I host this? I think through that entire ecosystem beyond copilots. That’s where innovation can kick in, and that broader talent strategy is something I’m working with my customers on. On collaboration: I heard a panel discussion recently, and a question was asked about what’s the number-one trait CIO needs to be successful at in the world of AI, and the answer was collaboration. You need to bring everybody together, move forward together, and make sure everybody’s on board. And in my mind, simplifying that is more like systems thinking when you operate, just bringing everybody along and ensuring they’re meeting outcomes. But maybe what’s more important is managing expectations. Because if you’re a CIO, there’s a tremendous amount of pressure to deliver and have a rock solid AI strategy. So what I’m doing with my customers is get the board, CEO, and CFO into a room and help them understand what I’m talking about, the evolution, and what’s the art of possible. You don’t want to be a CIO who thinks I have a hammer and everything is a nail. Having buy in from the senior leaders is essential to know you’re headed in the right direction. You’re not reacting to pressure from top leadership, but driving and becoming the change agent for good for the company. On navigating AI: It’s interesting times. I’m covering a spectrum of startups, non-technical and technical founders, and advising Fortune 500 companies. What I’m seeing is they love the velocity and momentum because that’s what they’ve always wanted, and AI is providing that. They’re able to bring their products to markets very quickly, so something that would’ve taken three years a couple of years ago is probably now taking them three months. There’s a lot of excitement there. But on the flip side, the same velocity is also hurting them. There are so many frontier AI companies getting disrupted. OpenAI, for instance, has offerings in sales and marketing, and Google has an interactive video model. So a lot of startups working in the marketing space are getting stuck. A lot of what I’m focused on is working with founders, helping them pivot in the gen AI space, ensuring their systems and products are built and structured in the right manner. And on the enterprise space, what I’m seeing is the POC wave, and people have seen the value. There’s some excitement but now the struggle is getting them to production. That’s where you run into cost, latency, legal compliance, privacy issues, and customer concerns that if we get tickets to production, how’s it going to look and how are we going to scale. So engineering and product teams have to be ably supported by the enterprise architecture and R&D teams. I then help them get up to speed and build that internal platform product for the production workloads. It’s exciting times on both sides.
Score: 30🌐 MovesAug 12, 2026https://www.cio.com/article/4207836/where-it-leaders-find-strength-and-opportunity-in-the-age-of-ai.html - From hype to impact: Operationalising AI for scalable enterprise transformation
By Ganesan Karuppanaicker, Chief Technology Officer, Birlasoft The enterprise AI conversation has shifted from possibility to accountability. Over the last decade, artificial intelligence has moved from the margins of innovation […] The post From hype to impact: Operationalising AI for scalable enterprise transformation appeared first on Express Computer .
- I gave ChatGPT access to my mess of open Chrome tabs — and it turned my browser clutter into something genuinely useful
ChatGPT's new Side Chat features bring the AI directly into the pages you're already browsing.
- エージェント型自動化：AIエージェントがエンタプライズ・プロセス自動化を推進する
エージェント型自動化：AIエージェントがエンタプライズ・プロセス自動化を推進する Gartner
- 3 Value Stories for Justifying AI Implementation in RD
3 Value Stories for Justifying AI Implementation in R&D Gartner
- Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From
Enterprise Document Intelligence [Vol.1 #5nonies] - Nature, plan, execute, synthesize: closing brick 1 with a dispatcher that reads each PDF’s nature and picks the method that fits, fitz, Docling, PaddleOCR, EasyOCR, MinerU or Surya, then folds the outputs into one corpus The post Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From appeared first on Towards Data Science .
- Dan Ives Talks New Moves in the AI Revolution
After leaving Wedbush, Dan Ives has launched a new merchant bank that he says will deliver the same research he's known for, but with people who want to innovate and grow in this "Fourth Industrial Revolution." The wide-ranging conversation touches on AI skepticism, China's role in the AI industry, and why he sees the AI industry going to heights that we may not yet be able to see. (Source: Bloomberg)
Score: 30🌐 MovesAug 12, 2026https://www.bloomberg.com/news/videos/2026-08-12/dan-ives-talks-new-moves-in-the-ai-revolution-video - I wrote an AI textbook — how long until AI can do it better?
Reflections on AI's writing ability and how AI models get more capable.
- Why Stream ring-maker Sandbar says the future of AI wearables is voice
AI notetaking hardware has taken off over the past couple of years, with credit-card-sized devices, pendants, pins, and even transcribing earbuds all promising to capture your meetings and turn them into summaries and action items. Now, a whole wave of wearables — rings especially — are betting people want to capture stray thoughts and ideas the same way. One of […]
Score: 30🌐 MovesAug 12, 2026https://techcrunch.com/video/why-stream-ring-maker-sandbar-says-the-future-of-ai-wearables-is-voice/ - Booksellers suspect AI firms are buying and then destroying rare books
AI firms quietly bulk buying rare books face resistance from booksellers.
- Google Photos’ new Moods feature turns your existing images into retro film frames
Gosh, I feel old!
Score: 30🌐 MovesAug 12, 2026https://www.androidauthority.com/google-photos-film-camera-moods-3697527/ - Data center markets are booming in these EMEA countries
Data center markets are booming in these EMEA countries IT Pro
Score: 30🌐 MovesAug 12, 2026https://www.itpro.com/infrastructure/data-centres/the-data-center-market-is-booming-in-these-emea-countries - At Underscore's startup showcase, AI agents were all the rage
Four out of the seven startups that completed the fellowship program organized by Underscore to honor its late co-founder John Pearce are building agents or services for the AI world.
- Butterfly-inspired ceramic microscrolls unroll with magnets to power tiny robots
Researchers at the University of Stuttgart and the Max Planck Institute for Solid State Research have developed tiny rolls that can be unrolled and rolled up in a controlled manner using a magnet. The model for this was the proboscis of butterflies. These smart materials enable the development of more efficient drive technologies for micro- and soft robotics, a field of research of great economic importance. The results have been published in the journal Advanced Materials.
Score: 30🌐 MovesAug 12, 2026https://techxplore.com/news/2026-08-butterfly-ceramic-microscrolls-unroll-magnets.html - Podcast: Mark Zuckerberg’s 'Superintelligent' AI Future That No One Wants
Zuckerberg's anti-social future; a company offering human writing that is actually just AI; and the big switch from Flock to Axon.
Score: 30🌐 MovesAug 12, 2026https://www.404media.co/podcast-mark-zuckerbergs-superintelligent-ai-future-that-no-one-wants/ - ‘Unlocking’ the Evidence Act: Ex-feds’ AI tool aims to bring policy docs to life
The Data Foundation’s new AI assistant surfaces statistical evidence and policy-supporting data underpinning the ultra-dense 2018 law. The post ‘Unlocking’ the Evidence Act: Ex-feds’ AI tool aims to bring policy docs to life appeared first on FedScoop .