1996 or 1999? Walsh's First Test is 'How to View AI'

marsbit發佈於 2026-06-20更新於 2026-06-20

文章摘要

"1996 or 1999? Wall's First Big Test Is 'How to View AI'" Federal Reserve Chairman Wall's initial challenge is not whether to raise or cut rates, but a more fundamental judgment: what kind of boom is the current AI boom? This will determine the Fed's policy path and define his legacy. Economics is split between two opposing views, according to reporter Nick Timiraos. One sees imminent productivity gains that will increase supply and cool inflation, allowing the Fed to hold steady. The other argues that while productivity benefits are distant, demand shocks are here now, and waiting for data confirmation risks missing the intervention window, forcing sharper rate hikes later. Wall has signaled a leaning toward the first view, echoing 1996-era Alan Greenspan, who embraced strong, productivity-driven growth without fear of inflation. However, Wall faces a different macro environment than Greenspan did, with tariff pressures, expanding fiscal deficits, and diminishing globalization benefits, which could force more significant inflation pressures even if AI benefits materialize. Wall's logic, expressed before taking office, is that AI-driven productivity gains won't show in official data for years. If the Fed waits for confirmation, it might mistakenly tighten policy and choke off the very growth that could suppress inflation. This argues for using forward-looking narratives over lagging data. Chicago Fed President Austan Goolsbee presents a key counter-argument. He distingui...

Written by: Dong Jing

The foremost challenge facing Walsh upon becoming Fed Chairman is not whether to raise or lower interest rates, but a more fundamental judgment: What kind of boom is the current AI prosperity? This judgment will determine the Fed's policy direction and define Walsh's place in history.

On June 19, Nick Timiraos, known as the "New Fed Whisperer," reported that the economic community holds two diametrically opposed interpretations of the AI construction boom:

First, the productivity dividend is about to materialize, supply will catch up with demand, and the Fed can stand pat and wait for inflation to subside naturally; second, the benefits of productivity gains are still in the distant future, while the demand shock has already arrived. If the Fed waits for data confirmation, it will miss the optimal intervention window and ultimately be forced to raise rates more sharply.

While the Fed held rates steady this week, nearly half the officials in the latest dot plot still project rate hikes this year, with the rest holding the opposite view. This deep internal division reflects the high degree of uncertainty surrounding this core issue.

Walsh's own inclination was faintly visible at the press conference. He repeatedly emphasized "robust, productivity-driven growth is not something we fear, but something we embrace," an echo of Greenspan's 1996 thinking.

However, the macroeconomic environment he faces—tariff pressures, widening fiscal deficits, fading globalization dividends—is far removed from the smooth sailing of Greenspan's era. Making the correct judgment between these two historical scripts will be Walsh's first true test at the Fed's helm.

Two 1990s: The Dual Legacy Left by Greenspan

Timiraos indicates that Walsh has repeatedly invoked the 1990s as a historical reference over the past year, but that decade itself contains two very different stories.

In 1996, facing rapid economic expansion, Greenspan chose to stand pat. He judged that fast growth wouldn't ignite inflation, and history proved him right. The expansion continued for years, earning him the reputation of a "maestro."

In 1999, Greenspan changed his judgment. With soaring stock markets and a persistently tight labor market, he began a series of rate hikes, which culminated in the dot-com bubble burst. It was also in this year that the Fed established its "forward guidance" mechanism of signaling rate hikes in advance—a practice that continues to this day and one that Walsh has explicitly stated he wishes to abolish.

The Trump administration publicly favors the 1996 version of the Fed. Before taking office, Walsh also publicly expressed his desire to create a central bank "confident enough to do less." Yet, current economic conditions may be handing him a different version of the script.

Walsh's Judgment Logic: Believe the Narrative, Not Wait for the Data

Before taking office, Walsh publicly stated his position on Fox Business: He fears the Fed is about to make its "sixth or seventh major mistake"—tightening monetary policy too early in what should be a hands-off productivity boom.

Timiraos reports that his core argument is: Productivity gains from AI will not be immediately reflected in official statistics; it may take several years for them to show up. If the Fed insists on waiting for data confirmation, it risks misdiagnosing a benign boom as an overheating economy and raising rates—which would precisely choke off the growth momentum that could have subdued inflation.

The essence of this logic advocates using a forward-looking narrative instead of lagging data as the basis for decision-making. Walsh continued this line of thinking at the press conference: when asked whether AI is currently boosting demand or expanding supply, he merely stated "demand is easier to measure than supply," deliberately avoiding a clear stance while adhering to the principle of "not telegraphing the next move" in communication.

Timiraos believes that even if Walsh's ultimate judgment is correct, the 1990s analogy is not complete.

When Greenspan made his famous gamble in 1996, he had multiple tailwinds: cheap goods and labor from abroad continuously suppressed inflation, and the federal fiscal deficit was narrowing. These structural factors provided additional safety margins for the Fed's "wait-and-see" approach.

Walsh faces a markedly different environment: tariff policies are raising import costs, fiscal deficits are expanding rather than contracting, and globalization dividends have faded. This means that even if the AI productivity dividend ultimately materializes as expected, the inflationary pressure Walsh endures while waiting will far exceed what Greenspan faced back then.

Counterargument: The Chicago Fed's "Front-Loading of Expectations" Model

Timiraos points out that the most systematic challenge to Walsh's judgment logic comes from Chicago Fed President Austan Goolsbee.

According to a Wall Street Journal report, Goolsbee proposed a key distinction at a Stanford University conference last month: Whether a productivity boom allows a central bank to stand pat depends on whether the boom is unexpected. A boom that everyone can foresee can have the opposite effect—people will front-load their future wealth, increasing spending significantly before the productivity gains materialize, leading to economic overheating.

"You end up having to raise rates more than you would have had to if you had acted earlier," Goolsbee said.

He believes the current AI boom is precisely this type of "visible to all." Surveys of economists, tech workers, and the general public show the market widely expects AI to deliver about one percentage point of annual productivity gains, with most benefits still in the future. According to his model, this expectation itself constitutes a reason to raise rates, not a reason to cut.

Goolsbee also cited real-world "overheating signals": AI data center construction is driving up the prices of land, electricity, and chips, while also increasing costs for electricians and equipment, squeezing resources from other sectors. Apple's announcement this week of price hikes due to rising costs was cited by him as evidence this mechanism is at work.

It is worth noting that Goolsbee's framework is not without challengers. Fed Governor Christopher Waller, at the same Stanford conference, pointed out that the "front-loading of expectations" mechanism can work only if people are able to borrow to spend ahead. In reality, however, spending for many households is tightly constrained by current income, making it difficult to monetize future wealth easily.

"If they cannot front-load that spending, the whole mechanism gets shut off," Waller said.

This rebuttal provides theoretical support for Walsh's "stand pat" stance: If borrowing constraints are widespread enough, the demand-frontloading effect will be greatly diminished, making a productivity boom more likely to expand supply in a benign manner rather than triggering inflation.

Ultimate Paradox: Abolish Forward Guidance, or Be Forced to Use It

Furthermore, Timiraos argues that Walsh faces a deeper paradox at the Fed's helm, and this paradox stems precisely from what he most wants to change.

He has explicitly stated his desire to create a Fed that "does not show its cards in advance," reducing forward guidance and keeping markets guessing. However, the Fed's current forward guidance mechanism was established precisely in 1999—when Greenspan, to avoid catching markets off guard, began signaling rate hikes in advance.

If the economic trajectory is as optimistic as the Trump administration portrays, Walsh may never need to signal rate hikes early. But if the economy follows the other script, he will face a dilemma:

Either use the forward guidance convention he wishes to abolish, informing markets of rate hike plans in advance; or remain silent, letting markets guess the magnitude and pace of hikes, and bear the risk of severe financial market volatility that ensues.

The solution to this paradox ultimately still depends on the answer to the same question: Is it 1996, or 1999?

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相關問答

QWhat is the core challenge that Chairman Wash faces regarding AI, and how will it influence his policy decisions?

AThe core challenge is determining the nature of the current AI boom. He must judge whether it is a productivity-driven boom like in 1996 (where patience is warranted) or a demand-driven boom that risks overheating like in 1999 (requiring preemptive tightening). This fundamental judgment will dictate the Federal Reserve's monetary policy path, including decisions on interest rates, and ultimately define Wash's historical legacy.

QAccording to the article, what are the two contrasting interpretations of the AI boom within the economics community?

AThe two interpretations are: 1) Productivity dividends are imminent, supply will catch up with demand, and the Fed can hold steady while inflation naturally recedes. 2) The benefits of productivity gains are still distant, but the demand shock has already arrived. If the Fed waits for data confirmation, it will miss the optimal intervention window and eventually be forced to raise rates more aggressively.

QHow does Wash's personal logic on AI and productivity differ from a purely data-dependent approach?

AWash's logic advocates using a forward-looking narrative over lagging data for decision-making. He argues that AI's productivity gains won't be immediately visible in official statistics and may take years to show. If the Fed waits for data confirmation, it risks misjudging a benign productivity boom as economic overheating and raising rates, which would choke off the very growth that could suppress inflation.

QWhat is the key argument posed by Chicago Fed President Austan Goolsbee against Wash's 'wait-and-see' stance on the AI boom?

AGoolsbee argues that whether a productivity boom allows the Fed to hold steady depends on whether the boom is unexpected. A widely anticipated boom, like the current AI wave, can have the opposite effect. People might front-load future wealth by spending more before productivity gains materialize, leading to economic overheating. This dynamic, visible in rising costs for data centers and related inputs, creates a rationale for raising rates sooner, not later.

QWhat is the fundamental paradox Chairman Wash faces regarding the Fed's communication policy, as outlined in the article?

AThe paradox is rooted in Wash's desire to abolish the Fed's practice of forward guidance (pre-signaling policy moves). However, this very practice was established in 1999 to prevent market shocks. If the economy follows a 1999-like scenario requiring preemptive tightening, Wash faces a dilemma: either use the forward guidance he wants to end to prepare markets, or remain silent and risk significant market volatility as participants guess the Fed's next move. The solution depends on his judgment of whether the current era is more like 1996 or 1999.

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什麼是 $S$

什麼是 AGENT S

Agent S:Web3中自主互動的未來 介紹 在不斷演變的Web3和加密貨幣領域,創新不斷重新定義個人如何與數字平台互動。Agent S是一個開創性的項目,承諾通過其開放的代理框架徹底改變人機互動。Agent S旨在簡化複雜任務,為人工智能(AI)提供變革性的應用,鋪平自主互動的道路。本詳細探索將深入研究該項目的複雜性、其獨特特徵以及對加密貨幣領域的影響。 什麼是Agent S? Agent S是一個突破性的開放代理框架,專門設計用來解決計算機任務自動化中的三個基本挑戰: 獲取特定領域知識:該框架智能地從各種外部知識來源和內部經驗中學習。這種雙重方法使其能夠建立豐富的特定領域知識庫,提升其在任務執行中的表現。 長期任務規劃:Agent S採用經驗增強的分層規劃,這是一種戰略方法,可以有效地分解和執行複雜任務。此特徵顯著提升了其高效和有效地管理多個子任務的能力。 處理動態、不均勻的界面:該項目引入了代理-計算機界面(ACI),這是一種創新的解決方案,增強了代理和用戶之間的互動。利用多模態大型語言模型(MLLMs),Agent S能夠無縫導航和操作各種圖形用戶界面。 通過這些開創性特徵,Agent S提供了一個強大的框架,解決了自動化人機互動中涉及的複雜性,為AI及其他領域的無數應用奠定了基礎。 誰是Agent S的創建者? 儘管Agent S的概念根本上是創新的,但有關其創建者的具體信息仍然難以捉摸。創建者目前尚不清楚,這突顯了該項目的初期階段或戰略選擇將創始成員保密。無論是否匿名,重點仍然在於框架的能力和潛力。 誰是Agent S的投資者? 由於Agent S在加密生態系統中相對較新,關於其投資者和財務支持者的詳細信息並未明確記錄。缺乏對支持該項目的投資基礎或組織的公開見解,引發了對其資金結構和發展路線圖的質疑。了解其支持背景對於評估該項目的可持續性和潛在市場影響至關重要。 Agent S如何運作? Agent S的核心是尖端技術,使其能夠在多種環境中有效運作。其運營模型圍繞幾個關鍵特徵構建: 類人計算機互動:該框架提供先進的AI規劃,力求使與計算機的互動更加直觀。通過模仿人類在任務執行中的行為,承諾提升用戶體驗。 敘事記憶:用於利用高級經驗,Agent S利用敘事記憶來跟蹤任務歷史,從而增強其決策過程。 情節記憶:此特徵為用戶提供逐步指導,使框架能夠在任務展開時提供上下文支持。 支持OpenACI:Agent S能夠在本地運行,使用戶能夠控制其互動和工作流程,與Web3的去中心化理念相一致。 與外部API的輕鬆集成:其多功能性和與各種AI平台的兼容性確保了Agent S能夠無縫融入現有技術生態系統,成為開發者和組織的理想選擇。 這些功能共同促成了Agent S在加密領域的獨特地位,因為它以最小的人類干預自動化複雜的多步任務。隨著項目的發展,其在Web3中的潛在應用可能重新定義數字互動的展開方式。 Agent S的時間線 Agent S的發展和里程碑可以用一個時間線來概括,突顯其重要事件: 2024年9月27日:Agent S的概念在一篇名為《一個像人類一樣使用計算機的開放代理框架》的綜合研究論文中推出,展示了該項目的基礎工作。 2024年10月10日:該研究論文在arXiv上公開,提供了對框架及其基於OSWorld基準的性能評估的深入探索。 2024年10月12日:發布了一個視頻演示,提供了對Agent S能力和特徵的視覺洞察,進一步吸引潛在用戶和投資者。 這些時間線上的標記不僅展示了Agent S的進展,還表明了其對透明度和社區參與的承諾。 有關Agent S的要點 隨著Agent S框架的持續演變,幾個關鍵特徵脫穎而出,強調其創新性和潛力: 創新框架:旨在提供類似人類互動的直觀計算機使用,Agent S為任務自動化帶來了新穎的方法。 自主互動:通過GUI自主與計算機互動的能力標誌著向更智能和高效的計算解決方案邁進了一步。 複雜任務自動化:憑藉其強大的方法論,能夠自動化複雜的多步任務,使過程更快且更少出錯。 持續改進:學習機制使Agent S能夠從過去的經驗中改進,不斷提升其性能和效率。 多功能性:其在OSWorld和WindowsAgentArena等不同操作環境中的適應性確保了它能夠服務於廣泛的應用。 隨著Agent S在Web3和加密領域中的定位,其增強互動能力和自動化過程的潛力標誌著AI技術的一次重大進步。通過其創新框架,Agent S展現了數字互動的未來,為各行各業的用戶承諾提供更無縫和高效的體驗。 結論 Agent S代表了AI與Web3結合的一次大膽飛躍,具有重新定義我們與技術互動方式的能力。儘管仍處於早期階段,但其應用的可能性廣泛且引人入勝。通過其全面的框架解決關鍵挑戰,Agent S旨在將自主互動帶到數字體驗的最前沿。隨著我們深入加密貨幣和去中心化的領域,像Agent S這樣的項目無疑將在塑造技術和人機協作的未來中發揮關鍵作用。

871 人學過發佈於 2025.01.14更新於 2025.01.14

什麼是 AGENT S

如何購買S

歡迎來到HTX.com!在這裡,購買Sonic (S)變得簡單而便捷。跟隨我們的逐步指南,放心開始您的加密貨幣之旅。第一步:創建您的HTX帳戶使用您的 Email、手機號碼在HTX註冊一個免費帳戶。體驗無憂的註冊過程並解鎖所有平台功能。立即註冊第二步:前往買幣頁面,選擇您的支付方式信用卡/金融卡購買:使用您的Visa或Mastercard即時購買Sonic (S)。餘額購買:使用您HTX帳戶餘額中的資金進行無縫交易。第三方購買:探索諸如Google Pay或Apple Pay等流行支付方式以增加便利性。C2C購買:在HTX平台上直接與其他用戶交易。HTX 場外交易 (OTC) 購買:為大量交易者提供個性化服務和競爭性匯率。第三步:存儲您的Sonic (S)購買Sonic (S)後,將其存儲在您的HTX帳戶中。您也可以透過區塊鏈轉帳將其發送到其他地址或者用於交易其他加密貨幣。第四步:交易Sonic (S)在HTX的現貨市場輕鬆交易Sonic (S)。前往您的帳戶,選擇交易對,執行交易,並即時監控。HTX為初學者和經驗豐富的交易者提供了友好的用戶體驗。

1.8k 人學過發佈於 2025.01.15更新於 2026.06.02

如何購買S

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